Demand Management

He received his BS degree in from Cairo University in 2009. He is currently an RA, working for a research project on developing an innovative revenue management system for the hotel business. He was awarded the IEEE CIS Egypt Chapter's special award for his graduation project in 2009. Bayoumi is interested to research in machine learning and business analytics; and he is currently working on his MS on stock market prediction.

This paper presents a deterministic capacity expansion optimisation model designed for large regional or national water supply systems. The annual model selects, sizes and schedules new options to meet predicted demands at minimum cost over a multi-year time horizon. Options include: supply-side schemes, demand management (water conservation) measures and bulk transfers. The problem is formulated as a mixed integer linear programming (MILP) optimisation model. Capital, operating, carbon, social and environmental costs of proposed discrete schemes are considered. User-defined annual water saving profiles for demand management schemes are allowed. Multiple water demand scenarios are considered simultaneously to ensure the supplydemand balance is preserved across high demand conditions and that variable costs are accurately assessed. A wide range of supplementary constraints are formulated to consider the interdependencies between schemes (pre-requisite, mutual exclusivity, etc.). A two-step optimisation scheme is introduced to prevent the infeasibilities that inevitably appear in real applications. The model was developed for and used by the 'Water Resources in the South East' stakeholder group to select which of the 316 available supply schemes (including imports) and 511 demand management options (considering 272 interdependencies) are to be activated to serve the inhabitants of South East of England. Selected schemes are scheduled and sized over a 25 year planning horizon. The model shows demand management options can play a significant role in the region's water supply and should be considered alongside new supplies and regional transfers.

The congestion pricing is a measure of travel demand management to discourage car use with low public and political acceptability. In the Brazilian context, the Urban Mobility Policy considers this measure to mitigate the congestion. In this paper, we present an exploratory analysis to identify the characteristics considered important by Brazilian transport experts to the implementation of the congestion pricing. The residents assessed these characteristics to identify the preference and acceptability of this scheme in Belo Horizonte (Brazil). We obtained the data from a Web-based survey from experts and residents. With the results, we simulated scenarios reducing the number of private cars in order to evaluate the real benefits of congestion price in a real network. According to Brazilian transport experts, the congestion pricing can be an efficient and well-accepted demand management measure, if the profit subsidises the public transportation systems (bus and rail) and the infrast...

The implications of integrating CRM and RM strategies in the context of the hotel environment, however, have received little attention. The key questions that need to be addressed are: who should be targeted with CRM efforts and how will those efforts affect the RM process? This paper examines the relationship between CRM and RM. By means of the life time/profitability approach to customer segmentation proposed by Reinartz and Kumar in 2002, the appropriate customer segments to target with CRM efforts are identified and a supporting RM strategy is outlined for each segment. These include traditional RM, lifetime value-based pricing, availability guarantees and short-term and ad hoc promotions. The impact of these RM strategies on business processes in relation to customer segmentation, demand forecasting, information systems management and human resource management is addressed.

An increasingly complex and dynamic operating environment demands that restaurant operators leverage the wealth of data available to them to drive decisions that support sustained profitability. The goal of this article is to integrate academic research with developments in the field to provide restaurant operators with a comprehensive decision-making framework for restaurant revenue management (RRM). The framework promotes the systematic application of internally and externally generated data to support RRMrelated decisions. This framework reflects a broad vision of RRM that is concerned with driving long-term demand and sustained profitability in addition to supporting short-term revenue generation.

PurposeThe purpose of this paper is to focus on home care organization employees, and examine how the interaction between job demands (emotional demands, patient harassment, workload, and physical demands) and job resources (autonomy, social support, performance feedback, and opportunities for professional development) affect the core dimensions of burnout (exhaustion and cynicism).Design/methodology/approachHypotheses were tested with a cross‐sectional design among 747 Dutch employees from two home care organizations.FindingsResults of moderated structural equation modeling analyses partially supported the hypotheses as 21 out of 32 (66 per cent) possible two‐way interactions were significant and in the expected direction. In addition, job resources were stronger buffers of the relationship between emotional demands/patient harassment and burnout, than of the relationship between workload/physical demands and burnout.Practical implicationsThe conclusions may be particularly useful ...

Demand response is a cornerstone problem in electricity markets under climate change constraint. Most liberalized electricity markets have a poor track record at encouraging the deployment of smart meters and the development of demand response. In Europe, different models are considered for demand response, from a development under a regulated regime to a development under competitive perspectives. In this paper, focusing on demand response and smart metering for mid-size and small consumers, we investigate which types of market signals should be sent to demand manager to see demand response emerge as a competitive activity. Using data from the French power system over the last 8 years, we compare the possible market design options to allow demand response to develop. Our simulations demonstrate that with the current market rules, demand response is not a profitable activity in the French electricity industry. Introducing a reserve and/or capacity remuneration could bring additional revenues to demand response providers and improve incentives to put in place demand response programs in a market environment.

Portugal was the first country in Europe to join Great Britain in the Gold Standard, in 1854, having abandoned the principle of free gold convertibility in 1891. By elucidating the historical choice of the Gold Standard by the Portuguese authorities, and analysing its macroeconomic behaviour, we prove that it is a mistake to compare different monetary systems with the same indicators. Our examination of demand, supply and monetary shocks in the context of a VAR model confirm the idea of appropriate application of the principles of classical economics to the Gold Standard in Portugal. We also prove that the principles of demand management were not compatible with the functioning of the Gold Standard.

It is commonly assumed that intermittent demand appears randomly, with many periods without demand; but that when it does appear, it tends to be higher than unit size. Basic and well-known forecasting techniques and stock policies perform very poorly with intermittent demand, making new approaches necessary. To select the appropriate inventory management policy, it is important to understand the demand pattern for the items, especially when demand is intermittent. The use of a forecasting method designed for an intermittent demand pattern, such as Croston's method, is required instead of a simpler and more common approach such as exponential smoothing. The starting point is to establish taxonomic rules to select efficiently the most appropriate forecasting and stock control policy to cope with thousands of items found in real environments. This paper contributes to the state of the art in: (i) categorisation of the demand pattern; (ii) methods to forecast intermittent demand; and (iii) stock control methods for items with intermittent demand patterns. The paper first presents a structured literature review to introduce managers to the theoretical research about how to deal with intermittent demand items in both forecasting and stock control methods, and then it points out some research gaps for future development for the three topics.

A study aimed at identifying barriers for more efficient water management was carried out on the Yongding river basin (the Yongding being a tributary of the Hai river) in northern China. The basin suffers from severe water scarcity, whereby agricultural water demand is the largest water user with about 66% of the total demand. The study identified two main policy problems: inadequate use of efficient irrigation technologies and a far too low agricultural water price. The study elaborated on policy instruments that could be used to overcome these two policy problems and assessed them using the Planning-Oriented Sustainability Assessment Framework , which applies a novel application of the analytical hierarchy process to assess and interpret the individual preferences of interviewed stakeholders based on their experiences with the policy instruments. Respondents agreed that all the considered policy instruments can be implemented. Indeed, most of them are already implemented somewhere in China. However, respondents expect that high levels of effort are needed. For, while policy makers are perceived to accept these instruments, the public in rural communities may not be ready for change. Thus, the promotion of water saving technology appears likely to gain more public support than increased water prices.

Diabetes distress (DD) significantly burdens and negatively impacts self-management and health outcomes in patients with type 2 diabetes (T2D). Early detection and management of DD are crucial for effective T2D management. The Diabetes Distress Assessment System (T2-DDAS) is a recently validated tool for measuring DD, but its psychometric properties in non-Western populations, such as India, have not been evaluated. This study aimed to assess the validity and reliability of T2-DDAS in Indian patients with T2D. Data from 408 T2D patients enrolled in a one-year diabetes management program at the Freedom from Diabetes Clinic in Pune, India, from January to March 2024, were analyzed. Sociodemographic characteristics, medical history, and anthropometric parameters were extracted from existing records. T2-DDAS, previously validated in a Western population, was administered. Statistical analyses included descriptive statistics, Principal Component Analysis (PCA), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM), using IBM SPSS, R, and AMOS software. The T2-DDAS demonstrated good internal consistency (Cronbach's α = 0.91). CFA yielded satisfactory fit indices (χ² = 1036.92, RMSEA = 0.07, TLI = 0.905, CFI = 0.918), supporting the construct validity of T2-DDAS for the Indian population. The T2-DDAS is a valid and reliable tool for assessing DD in Indian patients with T2D.

Water productivity (WP) is reported lower in Pakistan when compared to the rest of the world. This paper investi-gates the factors responsible for low water productivity and demonstrates various irrigation techniques farmers could use for its improvement. A comprehensive questionnaire was designed, and 230 farmers were interviewed in a cotton-wheat area (Samundri-site I), a mixed crop area (Chiniot-site II), and a rice-wheat area (Hafizabad-site III) in Rechna Doab, Punjab, Pakistan. This survey found that the majority of farmers expressed major concerns about shortages of canal water, energy, and fertilizer. These issues were the main factors affecting their land and water productivity. Field experiments were conducted at the above mentioned sites. The results indicated that drip irrigation was the most efficient irrigation technique, which produced a maximum WP of 2.26 kg m-3 for wheat. Drip irrigation was 98% efficient, and water savings were 40% better when compared with that un...

Abstract: Understanding the characteristics of household electricity consumption and its driving factors under the changing cultural circumstances of society can be useful in designing proper regulations related to energy saving in households. This paper analyses the results of a field survey of the Indonesian households in making decisions about electrical devices use, with aim to understand the consumers' behavior in consuming electricity in order to give clear understanding of household electricity consumption ...

The demand for water-energy (WE) should be addressed with their sustainable supply in the long-term planning. The total energy demand was estimated to be around 14,000000 and 53,000000 MWh for 2030 and 2050 years respectively. These years’ predicted water demand was 0.4 and 0.7 billion-cubic-meter. Based on the estimated energy and water demand, sustainable supply through WE management were determined. In 2030 and 2050 the water supply-demand balance index is around 1, showed water demand will be met for respective years, whereas the energy supply-balance after the intervention become around 0.9 and 0.7. The study results clearly predicted future WE demand of Addis Ababa city and have been put their quantified supply suggestion.

This article contains an application of peak-load pricing rules to public water ser- vices. The model presents a standard water distribution system and a separate wastewater collection and treatment system. Technical and financial constraints are considered. The optimization process provides peak-load prices for drinking water and sewerage services. These prices reflect efficiently the costs of systems constraints and the real value of water resources scarcity. They provide important guidance in the design of efficient water rates and in the development of different water utilities planning strategies. New technologies in water metering (telemetry) should permit applying this model. Le pr6sent article contient un exemple d'application des rdgles de fixation de tarifs en periode de pointe pour les services d'eau publics. Le moddle pr6sente un r6seau de distribution d'eau type et un systt;me distinct de collecte et de traitement des eaux us6es. ll est tenu compte des contraintes techniques et financidres. Le processus d'optimisation offre des tarifs de p6riode de pointe pour l'eau potable et les services d'6ouration des eaux us6es. Ces tarifs refldtent efficacement les co0ts des contraintes des systdmes ainsi que la valeur r6elle de la raret6 des ressources hydriques. ll s'agit d'un outil important pour orienter l'6laboration d'une tarification efficace de l'eau et la mise au point de strategies de planification des services d'eau publics. De nouvelles technologies se rapportant aux compteurs d'eau (tel6mesure) devraient permettre l'application de ce modi;le.

Water one of the main sources for human survival and growth. The Government of India has recognized the importance of proper utilization of this very special solution and has mentioned the special challenges faced with its management. Through this research we have attempted to understand and evaluate the main causes of lack of proper water management in urban cities by using available literature as well involving the officials of local bodies involved in its management. In this research we collected opinions through an open-ended questionnaire from the people mostly involved in its management. The respondents were of the favor of setting up of boards and accountable bodies for proper management of resources.

Extreme weather phenomena are increasing due to climate change and having a severe impact on critical infrastructure, including airports. In this context, conducting climate risk assessments is an essential step to implement appropriate adaptation strategies. In the present study, a climate-risk assessment framework is applied to evaluate the risk of extreme precipitation events for specific Italian airports: Malpensa, Bergamo, Linate, Fiumicino, Ciampino, Napoli, Catania, Palermo, and Cagliari. This analysis is based on the definition of risk as reported by Sixth Assessment Report of IPCC. The assessment of the climate hazard over the recent-past period (1981-2010) is evaluated through indicators developed from re-analysis data, using the Uncertainties in Ensemble of Regional Re-Analyses dataset are provided by Copernicus Climate Change Service. The expected climate variations are evaluated using an ensemble of high-resolution climate projections from the EURO-CORDEX initiative for the short-(2021-2050), medium-(2041-2070), and long-term future period (2071-2100), under RCP 2.6, RCP 4.5, and RCP 8.5 climate scenarios. The information related to exposure and vulnerability indicators are collected from official documents and website of selected airports, and are freely available. The final risk index provides elements allowing stakeholders to implement adaptation measures to increase their resilience.

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This perspective demonstrates that household electricity usage is a good proxy for poverty and a quick, efficient, and effective targeting mechanism for welfare benefits. As Sri Lanka’s economic crisis continues, up to 50% or more of the population will likely need state support, yet the existing welfare benefit scheme falls far short of its goals. Current targeting through Samurdhi reaches just about a quarter of all households and only 40% of the poorest decile of individuals. The analysis presented in this perspective shows that the alternative of using a threshold of 60kwh of electricity usage per month as a preliminary eligibility criterion will reach approximately 50% of the population and over 80% of the poorest among them and performs best among a set of alternatives, including Samurdhi.

He received his BS degree in from Cairo University in 2009. He is currently an RA, working for a research project on developing an innovative revenue management system for the hotel business. He was awarded the IEEE CIS Egypt Chapter's special award for his graduation project in 2009. Bayoumi is interested to research in machine learning and business analytics; and he is currently working on his MS on stock market prediction.

In this report the authors develop a scenario for future developments in the transport sector and their implications for future demand. In developing a comprehensive mode-space-time coverage of the evolution of transport systems, the analysis indicates that present transport systems are approaching a number of limits: market saturation in leading countries and an increasing awareness of the social and environmental disbenefits associated with a further intensification in the use of present-day oil-based transport systems. The report describes an innovative scenario from a historical perspective, taking into account a number of institutional and physical constraints to significant future increases in the the car population and air travel demand at the global level.

Crowd-shipping promises social, economic, and environmental benefits covering a range of stakeholders. Yet, at the same time, many crowd-shipping initiatives face multiple barriers, such as network effects, and concerns over trust, safety, and security. This paper reviews current practice, academic research, and empirical case studies from three pillars of supply, demand, and operations and management. Drawing on the observed gaps in practice and scientific research, we provide several avenues for promising areas of applications, operations and management, as well as improving behavioral and societal impacts to create and enable a crowd-shipping system that is complex, yet, integrated, dynamic and sustainable.

This study attempted to address possible solutions to water demand management for the improvement of efficient use of a given volume of water while increasing water access to new users; application of water demand management tools both at the utility and end-user sides; and managing water losses in the distribution network which is a critical aspect of water demand management. The research was conducted in Garankuwa and Mabopane supplied by ODI Water Services in South Africa. This paper describes water resources in South Africa, water demand management tools in place and water supply to the ODI Water Services. It further presents data for the total purchases of water from Rand water and the final billed water at the utility, and water consumption patterns during the period of July to December 2009. This included attempts made to identify and quantify water losses in Garankuwa and Mabopane during the same period. Suggestions were made on how water losses can be reduced. In Garankuwa and Mabopane it was discovered that human perceptions on water demand management and water wastage through unaccounted-for-water together with the indigenous knowledge systems for the management of natural resources need to be altered as the country is water stressed.

The case for demand-driven research and development has received important considerations among governments, donors and programme implementing partners in development planning and implementation. Addressing demand is believed to be a bottom-top approach for designing and responding to development priorities and is good for achieving development outcomes. In this paper, we discuss the concept and application of demand driven research for development (DDRD) in Africa. We use evidence of six projects implemented under the BiomassWeb Project in Africa. We focus on parameters on level of engagement of stakeholders - whose demand is being articulated, the processes for demand articulation, capacity building and implementation processes, innovativeness of the project, reporting and sustainability of the project. We find that the nature of the institutions involved in articulation and implementation of demand-driven research and development projects and their partnerships influence the impa...

• There is considerable evidence to suggest increasing dependence on groundwater for water-supply in developing cities. This is occurring in response to population growth, accelerated urbanization trends, increasing per capita use, higher ambient temperatures and reduced security of river-intakes with climate change -and is facilitated by the generally modest cost of waterwells. Unfortunately there are no systematic and comprehensive data to quantify this trend, but it has been approximately estimated that mote than 1.5 billion urban dwellers worldwide currently rely on groundwater. • Those urban centres underlain and/or surrounded by high-yielding aquifers, of sufficient potential to provide a major component of utility water-supply, usually have better mains water-service levels and lower water-prices -because ready access to groundwater has allowed utilities to expand their water-supply production incrementally at relatively low cost in response to rising demand. This (and the fact that major aquifers often have deeper water-tables implying higher waterwell construction cost) generally tends to result in less private residential in-situ use of groundwater. But industrial and commercial use is often present and, in situations where municipal watersupply service remains inadequate, private operators sometimes develop local domestic water distribution systems (reticulated or tankered) based on urban waterwells (eg : Asuncion-Paraguay -GW-MATE Case Profile 3). • However, there are rarely sufficient groundwater resources within the urban area itself to satisfy the water-supply demands of larger cities, and resource sustainability thus often becomes an issue. This natural scarcity is sometimes aggravated by competition with use for irrigated agriculture. Moreover, groundwater quality may also be threatened by inadequately-controlled urban pollution pressures, especially given the close connection between wastewater handling, disposal or reuse and underlying phreatic groundwater (Figure ). • The growth in urban groundwater use is not restricted to cities with ready access to high-yielding aquifers but also widely occurs in situations where the utility water-supply is imported from a distant surface-water source of poor reliability or at high cost. This may result in the mushrooming of private in-situ waterwell construction as a result of poor (present or historic) municipal waterservice levels and/or high water prices. • In these cases in-situ private self-supply from groundwater widely represents a significant proportion of water 'actually received by users', and its presence thus has major implications for municipal water utilities. The construction and operation of private waterwells by some groups of residential consumer also signifies a 'willingness to pay' for more reliable water-supply -and raises the question as to whether municipal water-service utilities should make more effort to 'capture this potential income' through improving their service-levels directly by reduction of distribution leakage losses (and other forms of 'non-revenue' mains water).

Onsite electricity generation system in manufacturing has been traditionally considered an effective backup energy source to support the manufacturing operations when external power is not available due to natural disasters and/or power blackouts. Recently, with the increasing concerns of climate change and environmental protection, the contribution of using onsite generation system (OGS) to the manufacturing end use customers when they enroll in specific electricity demand response programs has also been gradually recognized. In this paper, we investigate the cost-effective OGS sizing problem for manufacturing practitioners when participating in Critical Peaking Pricing (CPP) demand response program. A Mixed Integer Non-Linear Programming (MINLP) formulation is proposed to identify the optimal size and utilization strategy of the OGS, as well as the corresponding production plan of the manufacturing system to minimize the overall energy related cost. Linearization strategy and metaheuristic algorithm are discussed for solving the proposed formulation with a reasonable computational cost and a good solution quality. A case study based on a real auto component manufacturing system and an existing CPP program is implemented to examine the effects of the proposed model. The results show that when utilizing the OGS appropriately sized, the total electricity related cost of the manufacturing system can be significantly reduced when participating in the CPP program.

Climate change and the increase of population pose challenges to ensuring suitable water supply in water-scarce regions. This work presents a comparative analysis of the watersupply approaches adopted in Los Angeles, Southeastern Spain, and Sydney. Results show a decrease in per-capita water use in the period 2000-2020, which reflects an improvement in water conservation. Social factors in the domain of hydropolitics and economic efficiency explain the divergence of water policies adopted. The adaptation to water scarcity and growing population in three regions of developed countries located in different continents sheds light on challenges facing the achievement of water security worldwide.

Fresh water is a finite and vulnerable resource, essential to sustain life, development and the environment. Since water sustains life, effective management of water resources demands a holistic approach, linking social and economic development with protection of natural ecosystems. Effective management links land and water uses across the whole of a catchment area or groundwater aquifer. Water development and management should be based on a participatory approach, involving users, planners and policy-makers on all levels. The participatory approach involves raising awareness of the importance of water among policy-makers and the general public. It means that decisions are taken at the lowest appropriate level, with full public consultation and involvement of users in the planning and implementation of water projects. Women play a central part in the provision, management and safeguarding of water. This pivotal role of women as providers and users of water and guardians of the living environment has seldom been reflected in institutional arrangements for the development and management of water resources. Acceptance and implementation of this principle requires positive policies to address women's specific needs and to equip and empower women to participate at all levels in water resources programmes, including decision-making and implementation, in ways defined by them. Water has an economic value in all its competing uses and should be recognized as an economic good. Within this principle, it is vital to recognize first the basic rights of all human beings to have access to clean water and sanitation at an affordable price. Past failure to recognize the economic value of water has led to wasteful and environmentally damaging uses of the resource. Managing water as an economic good is an important way of achieving efficient and equitable use, and encouraging conservation and protection of water resources.

This paper establishes the case for Electric Vehicle (EV) charging demand management through in-field demonstration, electricity network modelling and financial assessment. As part of the Victorian Government Electric Vehicle Trial, DiUS Computing demonstrated EV charging demand management using United Energy's Smart Grid. Modelling of the United Energy network by the University of Melbourne found that uncontrolled charging would require network augmentation once EVs are adopted by 10% of households. In contrast, managed charging would allow the network to support in excess of 50% uptake using existing capacity and infrastructure. Furthermore, the end-to-end EV charging demand management solution demonstrated by DiUS could be implemented for one tenth the cost of the network augmentation. Although success factors were identified during the demonstration that may serve as an input for demand management program design, electricity market arrangements may be the strongest determinant of adoption generally.

The water industry in Australia and international is involved in a period of significant change. The conventional roles of water and wastewater utilities are being redefined with the objectives of resource conservation and sustainable development added to existing responsibilities. Least cost planning (LCP) has emerged as the way forward for water utilities in regions where water conservation has become an objective or where ongoing supply expansion is constrained. It involves techniques for the design and evaluation of demand management programs and aims to compare demand-and supply-side options on an equivalent basis. The approach is based on the key ideas that: demand is for the services water provides rather than the actual volume supplied; and that a drop of water saved is equal to a drop supplied. This paper contends that LCP has much to offer the water sector beyond demand management. It is an approach that has potential for options assessment across the water cycle and can aid planning towards more sustainable outcomes within the sector. The paper concludes that LCP concepts and techniques will have worth in addressing the challenges of sustainable development for both urban water systems and catchment management.

Revenue management (RM) has been widely applied in capacityconstrained tourism industries to maximise revenue by effectively managing demand and capacity. To gain long-run profit, understanding customers' perceptions of RM practices is important. This study attempts to build a better understanding of customers' perceptions of RM practices in terms of familiarity and fairness in six tourism and hospitality industries: airlines, hotels, restaurants, golf clubs, galleries and museums and theme parks. In addition, the study examines customers' perceptions of capacity scarcity during highdemand seasons for the six industries.

This report provides an in-depth analysis of Tenaga Nasional Berhad's (TNB) restructured electricity tariffs in Peninsular Malaysia, effective July 1, 2025. It specifically focuses on the domestic sector, covering the key changes in the tariff structure, explaining how a household's bill is calculated, and presenting simulations demonstrating the financial impact on different domestic household types, including the perceived benefits of shifting electricity consumption habits.

Order acceptance under uncertainty is a critical decision-making problem at the interface between customer relationship management and production planning of order-driven manufacturing systems. In this work, a novel approach for simulation-based development and on-line adaptation of a policy for dynamic order acceptance under uncertainty in make-to-order manufacturing using average-reward reinforcement learning is proposed. Locally weighted regression is used to generalize the gain value of accepting or rejecting similar orders regarding attributes such as product mix, price, size and due date. The order acceptance policy is learned by classifying an arriving order as belonging either to the acceptance set or to the rejection set. For exploitation, only orders in the acceptance set must be chosen for shop-floor scheduling. For exploration some orders from the rejection set are also considered as candidates for acceptance. Comparisons made with different order acceptance heuristics highlight the effectiveness of the proposed ARLOA algorithm to maximize the average revenue obtained per unit cost of installed capacity whilst quickly responding to unknown variations in order arrival rates and attributes.

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The Transportation Systems Analysis Model (TSAM) developed by Virginia Tech's Air Transportation Systems Lab and NASA Langley can provide detailed analysis of the effects on the demand for air travel of a full range of NASA and FAA aviation projects. TSAM has been used to project the passenger demand for very light jet (VLJ) air taxi service, scheduled airline demand growth and future schedules, Next Generation Air Transportation System (NGATS) benefits, and future passenger revenues for the Airport and Airway Trust Fund. TSAM can project the resulting demand when new vehicles and/or technology is inserted into the long distance (100 or more miles oneway) transportation system, as well as, changes in demand as a result of fare yield increases or decreases, airport transit times, scheduled flight times, ticket taxes, reductions or increases in flight delays, and so on. TSAM models all long distance travel in the contiguous U.S. and determines the mode choice of the traveler based on detailed trip costs, travel time, schedule frequency, purpose of the trip (business or non-business), and household income level of the traveler. Demand is modeled at the county level, with an airport choice module providing up to three airports as part of the mode choice. Future enplanements at airports can be projected for different scenarios. A Fratar algorithm and a schedule generator are applied to generate future flight schedules. This paper presents the application of TSAM to modeling future scheduled air passenger demand and resulting airline schedules, the impact of NGATS goals and objectives on passenger demand, along with projections for passenger fee receipts for several scenarios for the FAA Airport and Airway Trust Fund.

Reinforcement learning (RL) is an area of machine learning concerned with how agents take actions to optimize a given long-term reward by interacting with the environment they are placed in. Some well-known recent applications include selfdriving cars and computers playing games with super-human performance. One of the main advantages of this approach is that there is no need to explicitly model the nature of the interactions with the environment. In this work, we present a new airline Revenue Management System (RMS) based on RL, which does not require a demand forecaster. The optimization module remains but works in a different way. It is theoretically proven that RL converges to the optimal solution; however, in practice, the system may require a significant amount of data (a booking history with millions of daily departures) to learn the optimal policies. To overcome these difficulties, we present a novel model that integrates domain knowledge with a deep neural network trained on GPUs. The results are very encouraging in different scenarios and open the door for a new generation of RMSs that could automatically learn by directly interacting with customers.

Integrating intermittent renewable energy sources into the power grid poses significant challenges to grid stability and reliability. This study examines the integration of Energy Storage Systems (ESS) into power grids to enhance stability and performance. A simulation framework was developed to analyze the technical and economic viability of Battery Energy Storage Systems (BESS) and Pumped Hydro Storage (PHS) systems. The results demonstrate the effectiveness of ESS in alleviating voltage fluctuations, frequency deviations, and grid disturbances. A diversified energy storage portfolio with optimized siting and innovative market mechanisms maximizes the benefits of ESS integration. The study reveals that BESS excel in rapid response times and scalability, while PHS systems offer superior economic benefits. This study pioneers a comprehensive simulation framework that integrates technical, economic, and regulatory aspects to optimise the integration of Energy Storage Systems (ESS), providing novel insights into maximising grid stability and performance amid the increasing integration of renewable energy. The findings provide valuable insights for policymakers, industry stakeholders, and researchers seeking to optimize energy storage strategies for resilient, sustainable, and efficient power systems.

The metropolitan city of Istanbul is becoming overcrowded and the demand for clean water is steeply rising in the city. The use of analytical approaches has become more and more critical for forecasting the water supply and demand balance in the long run. In this research, Istanbul's water supply and demand data is collected for the period during 2006 and 2014. Then, using an autoregressive integrated moving average (ARIMA) model, the time series water supply and demand forecasting model is constructed for the period between 2015 and 2018. Three important sustainability metrics such as water loss to supply ratio, water loss to demand ratio, and water loss to residential demand ratio are also presented. The findings show that residential water demand is responsible for nearly 80% of total water use and the consumption categories including commercial, industrial, agriculture, outdoor, and others have a lower share in total water demand. The results also show that there is a considerable water loss in the water distribution system which requires significant investments on the water supply networks. Furthermore, the forecasting results indicated that pipeline projects will be critical in the near future due to expected increases in the total water demand of Istanbul. The authors suggest that sustainable management of water can be achieved by reducing the residential water use through the use of water efficient

Different methodologies are available for clustering purposes. The objective of this paper is to review the capacity of some of them and specifically to test the ability of self-organizing maps (SOMs) to filter, classify, and extract patterns from distributor, commercializer, or customer electrical demand databases. These market participants can achieve an interesting benefit through the knowledge of these patterns, for example, to evaluate the potential for distributed generation, energy efficiency, and demand-side response policies (market analysis). For simplicity, customer classification techniques usually used the historic load curves of each user. The first step in the methodology presented in this paper is anomalous data filtering: holidays, maintenance, and wrong measurements must be removed from the database. Subsequently, two different treatments (frequency and time domain) of demand data were tested to feed SOM maps and evaluate the advantages of each approach. Finally, the ability of SOM to classify new customers in different clusters is also examined. Both steps have been performed through a well-known technique: SOM maps. The results clearly show the suitability of this approach to improve data management and to easily find coherent clusters between electrical users, accounting for relevant information about weekend demand patterns.

This paper presents a deterministic capacity expansion optimisation model designed for large regional or national water supply systems. The annual model selects, sizes and schedules new options to meet predicted demands at minimum cost over a multi-year time horizon. Options include: supply-side schemes, demand management (water conservation) measures and bulk transfers. The problem is formulated as a mixed integer linear programming (MILP) optimisation model. Capital, operating, carbon, social and environmental costs of proposed discrete schemes are considered. User-defined annual water saving profiles for demand management schemes are allowed. Multiple water demand scenarios are considered simultaneously to ensure the supplydemand balance is preserved across high demand conditions and that variable costs are accurately assessed. A wide range of supplementary constraints are formulated to consider the interdependencies between schemes (pre-requisite, mutual exclusivity, etc.). A two-step optimisation scheme is introduced to prevent the infeasibilities that inevitably appear in real applications. The model was developed for and used by the 'Water Resources in the South East' stakeholder group to select which of the 316 available supply schemes (including imports) and 511 demand management options (considering 272 interdependencies) are to be activated to serve the inhabitants of South East of England. Selected schemes are scheduled and sized over a 25 year planning horizon. The model shows demand management options can play a significant role in the region's water supply and should be considered alongside new supplies and regional transfers.

The relationship between water abstraction and water availability has turned into a major stress factor in the urban exploitation of water resources. The situation is expected to be sharpened in the future due to the intensity of extreme meteorological phenomena, and socio-economic changes affecting water demand. In the city of Volos, Greece, the number of water counters has been tripled during the last four decades. This study attempts to simulate the city's network, supply system and water demand through a forecasting model. The forecast was examined under several situations, based on climate change and socio-economic observations of the city, using meteorological, water pricing, users' income, level of education, family members, floor and residence size variables. The most interesting outputs are: (a) the impact of each variable in the water consumption and (b) water balance under four management scenarios, indicating the future water management conditions of the broader ...

This research develops a demand management system, incorporating a machine-rate model, a rough-cut capacity planning (RCCP) model, and a demand management model for the fishing-net production industry. The machine-rate model is used to calculate a machine workload for the RCCP model to estimate capacity utilisation. The demand management model is important for quick response to customers' demands under a make-to-order (MTO) environment, such as that of the fishing-net production industry which has high variable demand requirements when compared to other industries. The demand management system has been successfully implemented in a fishing-net production company; and a simulation model is used to illustrate its effectiveness for demand management. The results indicate that the average profit per metric ton could increase from US$1,211 to US$1,353, approximately 11.7%. Moreover, the service level would be increased from 80.86% to 97.70%.

The world uses about 20 trillion kilowatt hours of electricity annually. Because of this great level of necessity, the use of green energy is growing and is becoming more and more significant in today's society. Demand-side management (DSM) programs are described as the procedures for planning, carrying out, and overseeing the tasks assigned by electric utilities to encourage customers to adjust their loads and energy usage in order to reduce power consumption and lower their electricity costs. It is utilized in smart grid systems to balance energy generation and consumption in a way that benefits both customers and utilities, to achieve the goals of utility energy policies, and to modify the quantity and quality of power and electricity used. Customers should have the capacity to control their energy consumption, especially during peak usage, to enable them to make better informed decisions. Demand response (DR) and energy efficiency techniques were employed by DSM to assist energy users in lowering their consumption. to increase resilience, economy, sustainability, and efficiency. The main objective of this study is to apply two demand side management strategies, examine power flow analysis on distribution networks utilizing IEEE rules both before and after PV cells are integrated, and assess the impact of doing so. The approaches' practicality is confirmed by comparing the simulation results from one technique with the other. For the end user, lowering their electricity cost is their primary goal.

Emphasis on effective demand management is becoming increasingly recognized as an important factor in operations performance. Operations models that account for supply costs and constraints as well as a supplier's ability to influence demand characteristics can lead to an improved match between supply and demand. This paper presents a new class of optimization models that allow a supplier to select, from a set of potential markets, those markets that provide maximum profit when production/procurement economies of scale exist in the supply process. The resulting optimization problem we study possesses an interesting structure and we show that although the general problem is N P-complete, a number of relevant and practical special cases can be solved in polynomial time. We also provide a computationally very efficient

Water scarcity in Iran has reached a level that calls for the attention of all stakeholders including water consumers. While government as water distributor has made significant efforts in managing water at the supply side, an annual average rainfall of 251 mm (Iran Meteorological Organization, 2008) limits the capacity of this supply-side approach. As a result, policy efforts have increasingly turned towards demand management approaches. The objective of this paper is to estimate drinking tap water demand for the households in Larestan. We determine the willingness to pay (WTP) for drinking taps water connections by the Larestan's households, using contingent valuation method (CVM). We use data from 320 randomly selected households in Larestan, Iran. Our findings show that, once drinking tap water connected, the households are willing to pay US$0.24 on average in addition to their monthly charge for per cubic meter water consumed.

As the third millennium begins, society faces the task of creating a transportation system that expands the energy resources available for mobility while reducing negative effects on the environment. This task is international in scope. Three critical issues-oil dependence, air pollution, and greenhouse gas emissions-confront the global transportation and energy system. Meeting these challenges will require energy-efficient technologies that are powered by improved energy sources. The technologies that determine transportation energy use now were invented roughly a century ago and were unforeseen a thousand years ago. Yet, the underlying needssociety's desire for ever more convenient and rapid access to goods and services-have persisted throughout history. Such desires will continue to shape transportation in the centuries ahead. The years approaching the new millennium have been marked by expansive innovation, offering vehicle and energy technologies that promise to meet both the underlying needs and the challenges posed. Implementing these new options must be accomplished ultimately through market choices. However, the market alone will not adequately address oil dependence, air pollution, and greenhouse gas emissions. New policies must be developed to guide technological and institutional changes toward a system for transportation energy that provides efficient mobility along with resource security and environmental sustainability. Transportation energy researchers will have an important role to play in assessing these issues in the decades ahead. Energy is essential to transportation. Conveying a person or thing from one place to another is equivalent to the scientific definition of work: force moving mass through distance. Energy is precisely the ability to do work or, in other words, the ability to transport. Energy, work, and transportation can be measured in the same terms (distance times mass). Thus, transportation's need for energy is as fundamental as the laws of physics. Since the Industrial Revolution, transportation has been a quest for ever-increasing speed, and this quest is likely to continue (1). Worldwide travel by fast modes of transportation such as air and high-speed rail could increase 20-fold by 2050 (2). Energy use tends to increase with the square of speed because the forces opposing motion (such as drag) also increase. So ensuring economical and environmentally sustainable transportation energy systems for a larger, wealthier, and faster-moving world will be an enormous undertaking.