Papers by Manoranjan Maiti
Pricing Policy with the Effect of Fairness Concern, Imprecise Greenness, and Prices in Imprecise Market for a Dual Channel
Springer proceedings in mathematics & statistics, 2023
Zenodo (CERN European Organization for Nuclear Research), Oct 2, 2022
In the competitive market, a customer's choice for an item depends on several factors like manage... more In the competitive market, a customer's choice for an item depends on several factors like management's marketing strategy and service, the item's price and greenness. Demand increases with the marketing strategy, service and item's greenness, but it is inversely related to the item's price. These relations are non-linear and imprecise. Recently, neutrosophic set has been introduced to represent impreciseness more realistically. Moreover, resources (capital, storage space, etc.) are generally uncertain (random or imprecise). Considering the above business scenarios, profit maximization EOQ models with price, marketing, service, and green dependent neutrosophic demand and order quantity dependent unit production cost are developed under different uncertain resource constraints. Models' parameters are pentagonal neutrosophic (PN) numbers. The proposed models are first made deterministic and then solved using the geometric programming technique. The PN parameters are made crisp using the score function. The random, fuzzy, rough and trapezoidal neutrosophic resource constraints in different models are converted to crisp using possibility measure, chance-constrained technique, trust measure and (α, β, γ)-cut with weighted mean, respectively. These processes reduce the objective function and constraints to signomial forms, and the reduced problems are solved by geometric programming technique with the degree of difficulty 2. Numerical experiments and sensitivity analyses are performed to illustrate the models.
RAIRO - Operations Research, 2019
An imperfect multi-item production system is considered against time dependent demands for a fini... more An imperfect multi-item production system is considered against time dependent demands for a finite time horizon. Here production is defective. Following [Khouja and Mehrez J. Oper. Res. Soc. 45 (1994) 1405–1417], unit production cost depends on production, raw-material and maintenance costs. Produced items have same fixed life-time. Warehouse capacity is limited and used as a constraint. Available space, production, stock and different costs are assumed as crisp or imprecise. With the above considerations, crisp and fuzzy constrained optimal control problems are formulated for the minimization of total cost consisting of raw-material, production and holding costs. These models are solved using conventional and fuzzy variational principles with equality constraint condition and no-stock as end conditions. For the first time, the inequality space constraint is converted into an equality constraint introducing a pseudo state variable following Bang Bang control. [Roul et al., J. Intel...
Yugoslav Journal of Operations Research, 2006
In this paper, a multi-item inventory model with space constraint is developed in both crisp and ... more In this paper, a multi-item inventory model with space constraint is developed in both crisp and fuzzy environment. A profit maximization inventory model is proposed here to determine the optimal values of demands and order levels of a product. Selling price and unit price are assumed to be demand-dependent and holding and set-up costs sock dependent. Total profit and warehouse space are considered to be vague and imprecise. The impreciseness in the above objective and constraint goals has been expressed by fuzzy linear membership functions. The problem is then solved using modified geometric programming method. Sensitivity analysis is also presented here.
International Journal of Computer Applications, 2014
In this paper, a realistic replenishment model with multiple warehouses (one is primary warehouse... more In this paper, a realistic replenishment model with multiple warehouses (one is primary warehouse (PW) from where the items are sold and others are secondary warehouses (SWs) where the items are stored) is developed with fuzzy lead-time under the assumption that the capacities of the warehouses are finite. Inflation and time value of money are taken into account. The items of secondary warehouses are transported to the primary warehouse in continuous release pattern and associated transportation cost is proportional to the distance from PW to SWs. The holding cost of items in SWs has reverse effect with distance. Here, the demand of items is a deterministic function of selling price and the displayed inventory. Deterioration rates of the items are constant and different in different warehouses. The replenishment rate is infinite and the problem is constructed with shortages, which are the mixture of back orders and lost sales. The backlogged demand is assumed to be a function of currently backlogged amount. When an item is out of stock, the loyal and captive customers will wait until the outstanding orders arrive and are served. To compensate the inconvenience of backordering and to secure orders, the supplier may offer a price discount on the stock out item. There are three scenarios depending upon the time when the new order is placed for the next cycle. The problem is illustrated with the help of numerical examples.
International Journal of Advanced Operations Management, 2014
In this paper, we concentrate on developing a bi-fuzzy multi objective transportation problem (MO... more In this paper, we concentrate on developing a bi-fuzzy multi objective transportation problem (MOSTP) according to bi-fuzzy expected value method (EVM). In a transportation model, the available discount is normally offered on items/criteria, etc., in the form all unit discount (AUD) or incremental quantity discount (IQD) or combination of these two. Here transportation model is considered with fixed charges and vehicle costs where AUD, IQD or combination of AUD and IQD on the price depending upon the amount is offered and varies on the choice of origin, destination and conveyance. To solve the problem, multi objective genetic algorithm (MOGA) based on Roulette wheel selection, arithmetic crossover and uniform mutation has been suitably developed and applied. To illustrate the models, numerical examples have been presented. Here, two types of problems are introduced and the corresponding results are obtained. To provide better customer service, the entropy function is considered.
Applied Mathematical Modelling, 2013
Zimmermann (Int. J. Gen. Syst. 2:209-215, 1976) first introduced the concept of fuzzy inequality ... more Zimmermann (Int. J. Gen. Syst. 2:209-215, 1976) first introduced the concept of fuzzy inequality in the field of linear programming problem (LPP). But this concept is hardly used in any real life applications of LPP. So, in this paper, a multi-objective multi-item solid transportation problem (MMSTP) with fuzzy inequality constraints is modeled. Representing different preferences of the decision maker for transportation, three different types of models are formulated and analyzed. Fuzzy inequality solid transportation problem is converted to parameter solid transportation problem by an appropriate choice of flexible index, and then the crisp solid transportation problem is solved by the algorithm (Cao in Optimal Models and Methods with Fuzzy Quantities, 2010) for decision values. Fuzzy interactive satisfied method (FISM), global criterion method (GCM) and convex combination method (CCM) are applied to derive optimal compromise solutions for MMSTP by using MatLab and Lingo-11.0. The models are illustrated with numerical examples and some sensitivity analysis is also presented.
Covering Solid Travelling Salesman Problem - An Algorithamic Study
Imprecise Constrained Covering Solid Travelling Salesman Problem with Credibility
Communications in computer and information science, 2017
In this article, we model an “Imprecise Constrained Covering Solid Travelling Salesman Problem wi... more In this article, we model an “Imprecise Constrained Covering Solid Travelling Salesman Problem with Credibility” (ICCSTSPC), a generalization of Covering Salesman Problem (CSP), in fuzzy environment. A salesman begins from an initial node, visits a subset of nodes exactly once using any one of appropriate vehicles available at each step, so that unvisited nodes are within a predetermined distance from the visited nodes, and returns to the initial node within a restricted time. Here the travelling costs and travelling times between any two nodes and the covering distance all are considered as fuzzy. Thus the problem reduces to find the optimal tour for a set of nodes with the proper conveyances so that total travelling cost is minimum within a restricted time. The ICCSTSPC is reduced to a set of Imprecise Constrained Covering Solid Travelling Salesman Problems by solving Unicost Set Cover Problem (USCP) using Random Insertion-Deletion (RID). These reduced Constrained Solid Travelling Salesman Problems (CSTSPs) are solved by an Improved Genetic Algorithm (IGA), which consists of probabilistic selection, order crossover, proposed generation dependent inverse mutation. A random mutation for vehicles is proposed to get a better cost at each generation of IGA by choosing an alternative vehicle for each node. Hence the ICCSTSPC is solved by a random insertion-deletion (RID) for covering set and IGA, i.e., RID-IGA. To justify the performance of the RID-IGA, some test problems are solved. The model is illustrated with some randomly generated crisp and fuzzy data.
Computers & Industrial Engineering, May 1, 2015
In this paper, a Modified Genetic Algorithm (MGA) is developed to solve Constrained Solid Travell... more In this paper, a Modified Genetic Algorithm (MGA) is developed to solve Constrained Solid Travelling Salesman Problems (CSTSPs) in crisp, fuzzy, random, random-fuzzy, fuzzy-random and bi-random environments. In the proposed MGA, for the first time, a new 'probabilistic selection' technique and a 'comparison crossover' are used along with conventional random mutation. A Solid Travelling Salesman Problem (STSP) is a Travelling Salesman Problem (TSP) in which, at each station, there are a number of conveyances available to travel to another station. Thus STSP is a generalization of classical TSP and CSTSP is a STSP with constraints. In CSTSP, along each route, there may be some risk/discomfort in reaching the destination and the salesman desires to have the total risk/discomfort for the entire tour less than a desired value. Here we model the CSTSP with traveling costs and route risk/discomfort factors as crisp, fuzzy, random, random-fuzzy, fuzzy-random and bi-random in nature. A number of benchmark problems from standard data set, TSPLIB are tested against the existing Genetic Algorithm (with Roulette Wheel Selection (RWS), cyclic crossover and random mutation) and the proposed algorithm and hence the efficiency of the new algorithm is established. In this paper, CSTSPs are illustrated numerically by some empirical data using this algorithm. In each environment, some sensitivity studies due to different risk/discomfort factors and other system parameters are presented.
GA-ABC hybridization for profit maximization of green 4DTSPs with discrete and continuous variables
Engineering Applications of Artificial Intelligence, Aug 1, 2023
Journal of uncertainty analysis and applications, Dec 1, 2013
In this paper, we introduce a new concept 'safety factor' in a transportation problem. When items... more In this paper, we introduce a new concept 'safety factor' in a transportation problem. When items are transported from plants to destinations through different conveyances, there are some difficulties/risks to transport the items due to bad road, insurgency, land slide, etc. in some routes. Due to these, a desired total safety factor is being introduced, and depending upon the nature of the safety factor, we develop five models. In this paper, a solid transportation problem (STP) with imprecise unit costs is considered. The sources' availabilities, destinations' demands, and capacities of conveyances are also represented by fuzzy numbers like trapezoidal and triangular numbers. The transportation problem has been formulated with and without a safety factor. To reduce the different models into its crisp equivalent, we introduce different methods as chance-constraint programming, an approach using interval approximation of fuzzy numbers and the application of the expected value model. Generalized reduced gradient technique is used to find the optimal solutions for a set of given numerical data. To illustrate the model, a numerical example has been presented and solved using LINGO.12 software. The effect of safety factors on transported amount is illustrated.
Emergent multipath COVID-19 specimen collection problem with green corridor through variable length GA
Expert Systems with Applications
Multiroute fresh produce green routing models with driver fatigue using Type-2 fuzzy logic-based DFWA
Expert Systems with Applications
An Opposition-based Genetic Algorithm for Multi-path Routing Problem with Risk
Soft Computing Research Society eBooks, 2021
A multi-path delivery system with random refusal against online booking using Type-2 fuzzy logic-based fireworks algorithm
Decision Analytics Journal
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
The objective of this investigation is to formulate a fixed charge (FC) solid transportation prob... more The objective of this investigation is to formulate a fixed charge (FC) solid transportation problem (STP) under a hybrid uncertain environment where both fuzziness and roughness coexist. A fuzzy rough STP model is developed by integrating the classical STP, fuzzy set theory, and rough set theory, which apparently provides a way to accommodate the uncertainty. For solving the problem, we apply the fuzzy rough expected value operator and propose the possibility based STP model with fuzzy rough parameters on a rough space. At the end, a mathematical illustration is provided to describe the fuzzy rough approach using LINGO 14.0 optimization software. As particular cases, the proposed model is also solved for single impreciseness. Finally, a graphical presentation is also shown to describe the comparison between two proposed approaches. In a particular case, the expressions of an earlier investigator have been derived from the present expressions. Important managerial decisions are made...
Recent Advances in Intelligent Information Systems and Applied Mathematics, 2020
In this paper, an innovative 4-dimensional multifarious breakable items transportation problem (4... more In this paper, an innovative 4-dimensional multifarious breakable items transportation problem (4DMBITP) has been proposed. Here, per unit selling expenses, per unit purchasing prices, per unit transportation expenditures, fixed charge, availability of the sources, demands of the destination, conveyances capacities and total available budget are expressed by rough intervals. The transported items are substitutable and complementary in nature. The demand of the items at the destination are directly related to the substitutability and complementary nature of the products and own selling price. The suggested model is converted into a deterministic one using lower and upper approximation intervals following Hamzehee et al. [1] as well as Expected Value Technique. The converted model is optimized through Generalized Reduced Gradient (GRG) techniques using LINGO 14 software. Finally, numerical examples are presented to illustrate the preciseness of the proposed model. Keywords: 4-dimensional TP • Rough interval • Substitutable and complimentary items • Fixed charge • Budget constraint
A Hybrid Heuristic for Restricted 4-Dimensional TSP (r-4DTSP)
In this paper, we proposed a hybridized soft computing technique to solve a restricted 4-dimensio... more In this paper, we proposed a hybridized soft computing technique to solve a restricted 4-dimensional TSP (r-4DTSP) where different paths with various numbers of conveyances are available to travel between two cities. Here, some restrictions on paths and conveyances are imposed. The algorithm is a hybridization of genetic algorithm (GA) and swap operator-based particle swarm optimization (PSO). The initial solutions are produced by proposed GA which used as swarm in PSO. The said hybrid algorithm (GA-PSO) is tested against some test functions, and efficiency of the proposed algorithm is established. The r-4DTSPs are considered with crisp costs. The models are illustrated with some numerical data.
Computers & Industrial Engineering, 2020
In the present formulation of the traveling purchaser problem (TPP), multiple vehicles exist in e... more In the present formulation of the traveling purchaser problem (TPP), multiple vehicles exist in each market to provide transport. In addition to minimizing the total cost, a second objective is to control the total emissions for the entire process. For the transportation of goods/items after their purchase, there are two possibilities: The articles purchased at each market may be either sent to the wholesaler's warehouse depot from the market by appropriate vehicles or transported together with the purchaser for the entire route in an appropriate goods vehicle. The appropriate conveyance is chosen on the basis of its cost and greenhouse gas (GHG) emissions. The total GHG emissions for the entire route and transportation of goods is subject to a constraint and, if it is more or less than the government authorized limit, the cap-and-trade policy is followed. In this study, two substitutes were considered. To mimic the reality, the travel and transport costs are assumed to be imprecise and are introduced as fuzzy numbers. To obtain a solution, a quantum-inspired genetic algorithm (GA) (Q i GA) was developed. This algorithm differs from others in that it includes quantum initialization, choice-based selection, and in vitro fertilization (IVF) crossover. To establish its effectiveness, a statistical test was performed. Illustrations of the models with numerical data are presented in this paper. Some managerial decisions are derived and, depending on the incentive and penalty structure for GHG emissions, a greener network design is presented to motivate the purchaser.
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Papers by Manoranjan Maiti