Latifa Dekhici

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Dr Latifa DEKHICI is an associate professor at informtics department in USTO-MB, Algeria.She is actually working in many optimization problems projects in many fields as healthcare system, power system and green transportation.

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Papers by Latifa Dekhici

Environmentally Friendly Energy Dispatching with the Interior Search Algorithm

Agent-Based Model for Interpreting a Client Query as Part of Composite Web Service Discovery

International Journal of Computing and Digital Systems

The use of new tools, such as ontologies and agents, is becoming increasingly important in Web se... more The use of new tools, such as ontologies and agents, is becoming increasingly important in Web services research as they can help us analyze requests and conduct semantic searches for Web services. The main goal of this study is to propose a solution for intelligently interpreting user queries when searching for Web services. The proposed model involves the collaboration of two primary agents: a reactive agent and a cognitive agent. The reactive agent analyzes the user's query and the cognitive agent reasons based on a relevant domain ontology, matching the concepts extracted from the query with the services already published in the UDDI registry. This approach allows for the intentions and desires of the user to be understood, and returns the most suitable service accordingly.

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Spatio-Temporal Graph for Improvement of Decision-Making in Risks Treatment

International Journal of Decision Support System Technology

Failures that hinder the proper functioning of complex systems are characterised by frequencies o... more Failures that hinder the proper functioning of complex systems are characterised by frequencies of occurrence, rates of evolution and variables periodicities. Indeed, a good design of this kind of systems requires the elaboration of an adapted analysis and modelling approach, which takes into account the spatial-temporal dynamics of the systems elements dysfunction. This paper proposes a Spatio-temporal modelling approach integrated into a risk management methodology. This modelling allows both to describe the evolution of the system in space and in time, and to follow the spatial and temporal scope of a failure of the system in order to improve decision making in choosing the appropriate corrective action. The elements of the methodology are illustrated and validated by a case study of a wireless sensor network system.

Application of Equilibrium Optimizer Algorithm for Solving Linear and non Linear Coordination of Directional Overcurrent Relays

Advances in Electrical and Electronic Engineering, Feb 28, 2023

In recent decades, the energy market around the world has been reshaped to accommodate the high p... more In recent decades, the energy market around the world has been reshaped to accommodate the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems' constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system is performed using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of simulation and statistical results of EO with other optimization techniques showed that EO is more effective and superior and provides the lowest optimization value in term of electric power generation, real power loss, emission index and voltage deviation.

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Techno-Economic Green Optimization of Electrical Microgrid Using Swarm Metaheuristics

Energies, Feb 11, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more

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Conception Optimale De La Fiabilite D'Un Parc Eolien

HAL (Le Centre pour la Communication Scientifique Directe), 2018

In this paper, the design objective is to maximize the reliability of the wind generation and pow... more In this paper, the design objective is to maximize the reliability of the wind generation and power transmission series-parallel system under cost and performance constraints using the firefly algorithm. We consider the system where redundant electrical components are selected to achieve a desirable level of reliability. The electrical components of each system are characterized by their reliability, capacity and cost. In order to assess the reliability of the system, the Ushakov method (UMGF) is used. The results show that the proposed method is effective in solving the problem of redundancy optimization and reliability. Dans cet article, l'objectif de la conception est de maximiser la fiabilité du système de production éolienne et le transport d'énergie parallèle-série sous les contraintes de coût et de performance en utilisant l'algorithme des lucioles. Nous considérons le système où les composants électriques redondants sont choisis pour atteindre un niveau de fiabilité souhaitable. Les composants électriques de chaque système sont caractérisés par leur fiabilité, capacité et leur coût. Afin d'évaluer la fiabilité du système, nous utilisons la méthode d'Ushakov (FGUM). Les résultats montrent que la méthode proposée est efficace pour résoudre le problème d'optimisation de redondance de la fiabilité.

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A Bi-Objective Paediatric Operating Theater Scheduling

International Journal of Healthcare Information Systems and Informatics, Jun 1, 2023

In this paper, a bi-objective Operating Theater scheduling is proposed. The problem is subject to... more In this paper, a bi-objective Operating Theater scheduling is proposed. The problem is subject to order and assignment constraints. The first objective is the minimization of the operating theater opening total time also called makespan in manufacturing systems while the second is to maximize constraints satisfaction. The scheduling problem is considered as a two-stage hybrid flow shop with blocking. Several metaheuristics are compared: the firefly algorithm, bats algorithm, particles swarm optimization and local search. In addition to the care specific qualitative and quantitative parameters, the average deviation from the lower bound is used in order to confirm the effectiveness of the methods. The implementation is done on the operating theater of the paediatric hospital of Oran when it is properly and improperly sized.

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Algorithme de Lucioles pour le Soin à Domicile

International audienceThis work aims to solve the problem of home care rounds using a metaheurist... more International audienceThis work aims to solve the problem of home care rounds using a metaheuristic nature-inspired which is the Firefly Algorithm (FF). A good discretization and correction of the solution has been provided to maintain the advantages of such an algorithm on this combinatorial problem. Even if the problem is only an extension of the classical Time Windowed Vehicle Routing Problem (TWVRP), the human aspect hardens it so that any abuse of constraint may eliminate feasibility or decrease the quality of services. Hard constraints concern the precedence between cares and the synchronization of several cares of the same patient. Whereas soft constraints concern preferences in time windows. The problem in this work also takes into account overtime and the drudgery of home-based workers. The main objective is to minimize the total duration of the tour and maximize the satisfaction of the constraints. After weighting the maximization of the satisfaction of soft constraints an...

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Application of Equilibrium Optimizer Algorithm for Optimal Power Flow with High Penetration of Renewable Energy

Energies, 2020

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Métaheuristique des Lucioles Discrète pour les Flow Shop Hybrides

L'algorithme des lucioles est une métaheuristique récente bio-inspirée. Dans ce travail, nous vis... more L'algorithme des lucioles est une métaheuristique récente bio-inspirée. Dans ce travail, nous visons à fournir une version discrète de l'algorithme des lucioles pour l'ordonnancement d'un atelier de type flow shop flexibles (FSH). Nous comparons l'algorithme des lucioles discret proposé avec la recherche locale et l'optimisation par essaims de particules (PSO) que nous concevons avec les même principes et paramètres. La mise en oeuvre avec différents nombres de lucioles sur un flow shop flexible typique qui est le flow shop flexible à deux étages, montre que la métaheuristique proposée trouve les meilleurs makespan mais il prend un temps d'exécution inconsidérément plus élevé que l'algorithme PSO. ABSTRACT.. The Fireflies algorithm is a recent bio-inspired metaheuristic. In this work, we aim to provide a discrete version of the algorithm fireflies for scheduling a hybrid flow shop (FSH).We compare the discrete fireflies algorithm proposed with local search and particle swarm optimization (PSO) that we design with the same principles and parameters. Implementation with different numbers of fireflies on a typical flexible flow shop which is the two stage two hybrid flow shop, shows that the proposed metaheuristic find the best makespan but it takes an execution time unduly higher than the PSO algorithm.

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Simulation Approach for staffing the UHCO Maternity's Operating Theatre

… Journal of Basic and Applied Sciences, 2011

The aim of this study is to reorganize and simulate the operating theatre of the maternity servic... more The aim of this study is to reorganize and simulate the operating theatre of the maternity service of the UHCO (University Hospital Centre of Oran) in order to improve quality and quantity performance. For this we use ASDI methodology which is based on the independence between knowledge and action models. We use ARIS Toolkit for the knowledge model and ARENA for simulating. After simulation of several scenarios, we have obtained satisfying results with addition of a nurse's aide and regrouping operating theatres of caesarian sections and gynecological operations in one block which were initially separated into two wings.

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Operating Theatre Scheduling Under Constraints

Journal of Applied Sciences, 2010

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Discretization of the Firefly Algorithm for Home Care

Canadian Journal of Electrical and Computer Engineering

This paper aims to solve the problem of home-care routing by using a metaheuristic inspired by na... more This paper aims to solve the problem of home-care routing by using a metaheuristic inspired by nature which is the firefly (FF) algorithm. A good discretization and correction of the solution was provided to maintain the advantages of such an algorithm on this combinatorial problem. Even if the problem is only an extension of the vehicle routing problem with time windows (TWVRP), the human aspect hardens it so that any abuse of a constraint can destroy the feasibility or reduce the services quality. Hard constraints concern the precedence between cares and a patient cares synchronization, while soft constraints concern time windows preferences. The problem in this paper also takes into account overtime and the painfulness of home workers. The main purpose is to minimize the routing total duration and to maximize the constraints satisfaction. The results on two examples show that the discrete version of the FF algorithm gives a better total travel time and better satisfies the constraints.

Reliability Maximization Using Firefly Algorithm under Performance and Budget Constraints

2188 Guerraiche et. al., Reliability Maximization Using Firefly Algorithm Under Performance and B... more 2188 Guerraiche et. al., Reliability Maximization Using Firefly Algorithm Under Performance and Budget Constraints Abstract— This paper uses firefly meta-heuristic to solve a constrained redundancy optimization problem (ROP). The ROP is a well known NP-hard optimization problem which has been the subject of many studies. Its resolution involves the selection of elements and redundancy levels to maximize the all system reliability or availability, under performance (capacity) and budget constraints. The system uses elements chosen from a list of available products to provide redundancy to increase system performance and reliability. A fast universal generating moment function (UMGF) technique is applied and implemented to evaluate system availability. While a constrained firefly algorithm is combined to it and adapted in order to optimize the problem. Results given on an illustrative example by the new method are compared with those of previous meta-heuristics (Ant Colony and Harmony...

Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm

Energies

The design of energy systems is very important in order to reduce operating costs and guarantee t... more The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm is based on the hybridization of two metaheuristics, which are the bat algorithm (BA) and the generalized evolutionary walk algorithm (GEWA), also called BAG (bat algorithm with generalized flight). The approach is combined with the Ushakov method, the universal moment generating function (UMGF), to evaluate the reliability of the multi-state series-parallel system. The multi-objective design aims to minimize the design cost, and to maximize the reliability and the performance of the electric power generation system from solar and gas generators by taking into account the reliability indices. Power subsystem devices are labeled according to their reliabilities, costs and performances. Reliability hangs on ...

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Green Capacited Vehicles Routing Optimization with Constraints Rule-Based Approach

A large quantity of air pollution is caused by the combustion of fuel. The Green Capacited Vehicl... more A large quantity of air pollution is caused by the combustion of fuel. The Green Capacited Vehicle Routing Problem (GCVRP) is an extension of Vehicle Touring (VRP) that aims to minimize fuel or CO2 emissions or fuel consumption instead of total distance or with it in case of bi-objective optimization. The objective of the present work is to resolve the GCVRP with heterogeneous vehicles through a rule-based approach combined to an oriented object design. This technique using an existing environment that is Optaplanner. The modularity of the environment separates design and heuristics such as tabu search in java, rules and objective function in drools language, heuristics’ setting in xml from data and results in excel files. Moreover, it appears very useful to the resolution of the Green Capacited Vehicles Routing Problem. In this paper, the resolution was investigated on a customized Belgic dataset taken from an existing benchmark. The instance contains 50 cities. The final project w...

Programmation Orientée Objet (POO)

Firefly Algorithm for Economic Power Dispatching With Pollutants Emission

Bio-inspired algorithms become among the most powerful algorithms for optimization. In this paper... more Bio-inspired algorithms become among the most powerful algorithms for optimization. In this paper, we intend to provide one of the recent bio-inspired metaheuristic which is the Firefly Algorithm (FF) to optimize power dispatching. For evaluation, we adapt the particle swarm optimization to the problem in the same way as the firefly algorithm. The application is done in an IEEE-14 and on two thermal plant networks. In one of the examples, we neglect power loss and pollutant emissions. The comparison with the particle swarm optimization (PSO), demonstrate the efficiency of firefly algorithm to reach the best cost in less than one second.

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Reliability optimization of wind farm power systems using bat algorithm with generalized flight

International Journal of Reliability, Quality and Safety Engineering

In this paper, two metaheuristics, namely the Bat algorithm (BAT) and a recent hybridization of b... more In this paper, two metaheuristics, namely the Bat algorithm (BAT) and a recent hybridization of bat algorithm with generalized walk evolutionary algorithm are presented. The bat algorithm and the Bat algorithm with generalized flight (BAG) are used to solve the problem of optimal redundancy design of series-parallel electrical systems. In order to assess the reliability of the heterogeneous system of multi-state series-parallel, the Ushakov method a universal moment generating function (UMGF) is used to allow fast estimation. The design objective is to maximize the reliability of the bulk power generation system from wind farm. The components of each electrical subsystem are characterized by their performance (capacity), cost and reliability. Reliability is defined as the ability to satisfy consumer demand that is given by a cumulative load curve. By comparing three algorithms cited in this study, the results show that the hybridization of Bat and Generalized Evolutionary Walk Algor...

Bat Algorithm With Generalized Fly for Combinatorial Production Optimization Problems

Advances in Knowledge Acquisition, Transfer, and Management, 2019

A set of metaheuristics has proved its efficiency in solving rapidly NP-hard problems. Several co... more A set of metaheuristics has proved its efficiency in solving rapidly NP-hard problems. Several combinatorial and continuous optimization areas drew profit from these powerful alternative techniques. This chapter intends to describe a discrete version of bat algorithm (BA) combined to generalized walk evolutionary (GEWA), also called bat algorithm with generalized fly or walk (BAG) in order to solve discrete industrial optimization. The first case of study is the well-known hybrid flow shop scheduling. The second one concerns the operating theatre that represents a critical manufacturing system, as the products delivered are patients. The last problem is the redundancy optimization (ROP) for series-parallel multi-state power system (MSS). Its resolution involves the selection of components with an appropriate level of redundancy to maximize system reliability with constrained cost. A universal moment generating function (UMGF) is used to estimate reliabilities. The modified bat algorithm on specific benchmarks was compared with the original one, and other results taken from the literature of each case study.

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Latifa Dekhici

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