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Optimization for a Sustainable Supply Chain Using Fuzzy VIKOR Method: An Application on a Real Dataset

IEEE ACCESS 2024年 12卷 131882-131891页

作者： Abhilasha, Anshu Danish, Faizan VIT AP Univ Sch Adv Sci Dept Math Amaravati 522237 Andhra Pradesh India

One of the main themes leading to a green economy is the sustainable supply chain, which creates the chance to lower carbon emissions all the way up the product value chain. Using a pharmaceutical company as a case study, this investigation explores optimized sourcing practices and proposes a methodology to help in selecting the best green supplier and place orders with potential suppliers. There is a two-phase hybrid method in the suggested model. The Fuzzy VIKOR (Fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje) methodology is used in the first phase to rate and select possible suppliers based on social, environmental, and economic factors (such as late delivery times and freight costs). The second phase describes an order allocation procedure based on (MOLP) multi-objective linear programming that aims to minimize costs, delivery delays, and greenhouse gas emissions during transportation. Using epsilon-constraint method we apply MOLP model to optimize more than one objective in order to convert two objectives into single objective function. Forming such a model is helpful for the manufacturing unit to evaluate green supplier and allocate order, as illustrated by a case study of a pharmaceutical manufacturing facility. Three suppliers are evaluated who used ocean, air and truck as their mode of transportation. Using Fuzzy VIKOR technique suppliers are evaluated and it is observed that the 'suppliers who supply medicines through ship is the best supplier. It is observed that transportation via ocean is more environment friendly in comparison of truck and airplane.

关键词： Pharmaceuticals Green products Resource management Carbon dioxide Supply chains linear programming Transportation Fuzzy systems Sustainable development & varepsilon -constraint method fuzzy VIKOR multi objective linear programming sustainable supplier selection

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multi-objective linear programming with interval coefficients A fuzzy set based approach

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KYBERNETES 2013年第3期42卷 482-496页

作者： Hajiagha, Seyed Hossein Razavi Mahdiraji, Hannan Amoozad Hashemi, Shide Sadat Inst Trade Studies & Res Dept Syst & Prod Studies Tehran Iran Islamic Azad Univ Kashan Branch Dept Management Kashan Iran

Purpose - The purpose of this paper is to extend a methodology for solving multi-objective linear programming (MOLP) problems, when the objective functions and constraints coefficients are stated as interval numbers. Design/methodology/approach - The approach proposed in this paper for the considered problem is based on the maximization of the sum of membership degrees which are defined for each objective of multi objective problem. These membership degrees are constructed based on the deviation from optimal solutions of individual objectives. Then, the final model based on membership degrees is itself an interval linear programming which can be solved by current methods. Findings - The efficiency of the solutions obtained by the proposed method is proved. It is shown that the obtained solution by the proposed method for an interval multi objective problem is Pareto optimal. Research limitations/implications - The proposed method can be used in modeling and analyzing of uncertain systems which are modeled in the context of multi objective problems and in which required information is ill defined. Originality/value - The paper proposed a novel and well-defined algorithm to solve the considered problem.

关键词： multi objective linear programming Interval numbers Order relations Membership degree Pareto optimallity linear programming Fuzzy logic programming and algorithm theory Modelling Decision making

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Optimization of a residential community's curtailed PV power to meet distribution grid load profile requirements

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RENEWABLE ENERGY 2023年 218卷

作者： Dellaly, Mariem Skander-Mustapha, Sondes Slama-Belkhodja, Ilhem Univ Tunis El Manar Ecole Natl Ingn Tunis LR11ES15 Lab Syst Elect Tunis 1002 Tunisia Univ Carthage Ecole Natl Architecture & Urbanisme Lab Syst Elect Tunis 1002 Tunisia

The integration of a large number of photovoltaic systems into the electricity grid presents significant technical challenges. To address the issue of excess power injection into the grid, various standards recommend curtailment of PV systems, which results in penalizing renewable energy. This paper proposes a solution to the problem without resorting to curtailment. The key innovation is to optimize the energy injected into the grid, achieving a delicate balance between benefits for prosumers and the grid operator, while also avoiding PV curtailment. The results obtained underscore substantial advantages for prosumers when contrasted with commercial solutions that resort to curtailing PV power, while ensuring the alignment of interests with network providers. The pro-posed energy management system is based on a multi-objective linear programming algorithm and aims to in-crease energy injection into the grid during peak regional demand while simultaneously considering the electricity price profile. The study utilizes digital twin technology to establish a dependable framework for validating proposed algorithms and comparing simulated results with experimental ones. By doing so, this process guarantees the accuracy of simulation results and allows for informed decision-making regarding the system under investigation.

关键词： PV power curtailment Energy management system multi objective linear programming Photovoltaic systems Microgrid Digital twin

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A novel lexicographic optimization method for solving shortest path problems with interval-valued triangular fuzzy arc weights

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020年第1期39卷 1277-1287页

作者： Ebrahimnejad, Ali Tabatabaei, Somayeh Santos-Arteaga, Francisco J. Islamic Azad Univ Qaemshahr Branch Dept Math Qaemshahr Iran Islamic Azad Univ Dept Math Firouzabad Iran Free Univ Bolzano Fac Econ & Management Bolzano Italy

Shortest path (SP) optimization problems arise in a wide range of applications such as telecommunications and transportation industries. The main purpose of these problems is to find a path between two predetermined nodes within a network as cheaply or quickly as possible. Conventional SP problems generally assume that the arc weights are defined by crisp variables, though imprecise data have been lately incorporated into the analysis. The present study formulates the SP problem in a directed interval-valued triangular fuzzy network. The resulting interval-valued fuzzy SP (IVFSP) problem is converted into a multi objective linear programming (MOLP) problem. Then, a lexicographic optimization structure is used to obtain the efficient solution of the resulting MOLP problem. The optimization process confirms that the optimum interval-valued fuzzy shortest path weight preserves the form of an interval-valued triangular fuzzy number. The applicability of the proposed approach is illustrated through an example dealing with wireless sensor networks.

关键词： Shortest path problem interval-valued triangular fuzzy numbers lexicographic optimization structure multi objective linear programming wireless sensor networks

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A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia

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SOCIO-ECONOMIC PLANNING SCIENCES 2018年 61卷 70-89页

作者： Tavana, Madjid Ebrahimnejad, Ali Santos-Arteaga, Francisco J. Mansourzadeh, Seyed Mehdi Matin, Reza Kazemi La Salle Univ Business Syst & Analyt Dept Distinguished Chair Business Analyt Philadelphia PA 19141 USA Univ Paderborn Fac Business Adm & Econ Business Informat Syst Dept D-33098 Paderborn Germany Islamic Azad Univ Qaemshahr Branch Dept Math Qaemshahr Iran Free Univ Bolzano Sch Econ & Management Bolzano Italy Univ Complutense Madrid Inst Complutense Estudios Int Pozuelo Spain Univ Mazandaran Dept Math Babol Sar Iran Islamic Azad Univ Karaj Branch Dept Math Karaj Iran

Data envelopment analysis (DEA) is generally used to evaluate past performance and multi objective linear programming (MOLP) is often used to plan for future performance goals. In this study, we establish an equivalence relationship between MOLP problems and combined-oriented DEA models using a direction distance function designed to account for desirable and undesirable inputs and outputs together with uncontrollable variables. This equivalence model can be effectively used to support interactive processes and performance measures designed to establish future performance goals while taking into account the preferences of decision makers (DMs). In particular, it allows DMs to consider different efficiency improvement strategies when subject to budgetary restrictions. The applicability of the proposed method and the efficacy of the procedures and algorithms are demonstrated using a case study where the performance of high schools in the City of Philadelphia is evaluated. (c) 2016 Elsevier Ltd. All rights reserved.

关键词： Data envelopment analysis Undesirable inputs and outputs Uncontrollable variables multi objective linear programming Interactive process Target unit

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multi-objective capacitated transportation problem with mixed constraint: a case study of certain and uncertain environment

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OPSEARCH 2018年第2期55卷 447-477页

作者： Gupta, Srikant Ali, Irfan Ahmed, Aquil Aligarh Muslim Univ Dept Stat & Operat Res Aligarh Uttar Pradesh India

In this paper, we have formulated a new model of multi-objective capacitated transportation problem (MOCTP) with mixed constraints. In this model, some objective functions are linear and some are fractional and are of conflicting in nature with each other. The main objective of this paper is to decide the optimum order of the product quantity which is to be shipped from source to the destination subject to the capacitated restriction on each route. Here the two situations have been discussed for the MOCTP model. In the first situation, we have considered that all the input information of the MOCTP model is exactly known and therefore a fuzzy goal programming approach have been directly used for obtaining the optimum order quantity of the product. While in the second situation the input information of the MOCTP model are uncertain in nature and this uncertainty have been studied and handled by the suitable approaches like trapezoidal fuzzy numbers, multi-choices, and probabilistic random variables respectively. Due to the presence of all these uncertainties and conflicting natures of objectives functions, we cannot solve this MOCTP directly. Therefore firstly we converted all these uncertainties into deterministic forms by using the appropriate transformation techniques. For this, the vagueness in MOCTP defined by trapezoidal fuzzy numbers has been converted into its crisp form by using the ranking function approach. multichoices in input information parameters have been converted into its exact form by the binary variable transformation technique. Randomness in input information is defined by the Pareto probability distribution, and for conversion into deterministic form chance constrained programming has been used. After doing all these transformations, we have applied fuzzy goal programming approach for solving this resultant MOCTP model for obtaining the optimum order quantity. A case study has been done to illustrate the computational procedure.

关键词： Capacitated transportation problem multi objective linear programming multi-objective fractional programming Fuzzy goal programming Mixed constraints multi-choice programming Chance-constrained programming Pareto distribution

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Optimization of transit bus fleet's life cycle assessment impacts with alternative fuel options

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ENERGY 2015年第Part1期93卷 323-334页

作者： Ercan, Tolga Zhao, Yang Tatari, Omer Pazour, Jennifer A. Univ Cent Florida Dept Civil Environm & Construct Engn Orlando FL 32816 USA Rensselaer Polytech Inst Dept Ind & Syst Engn Troy NY 12180 USA

Public transportation is one of the most promising transportation modes to reduce the environmental emissions of the transportation sector in the U.S. In order to mitigate the environmental impacts brought by the transit bus system, new energy buses are introduced into the vehicle market. The goal of this study is to find an optimal bus fleet combination for different driving conditions to minimize life cycle cost, greenhouse gas emissions, and conventional air pollutant emission impacts. For this purpose, a multi-objective linear programming approach is used to select the optimum bus fleet combinations. Given different weight scenarios, this method could effectively provide solutions for decision makers with various budget constraints or emission reduction requirements. The results indicate that in heavily congested driving cycles such as the Manhattan area, the battery electric bus is the dominant vehicle type, while the hybrid bus has more balanced performances in most scenarios because of its lower initial investment comparing to battery electric buses. Petroleum powered buses have seldom been selected by the model. The trade-off analysis shows that the overall greenhouse gas impact performance is sensitive to the life cycle cost after certain points, which could provide valuable information for the bus fleet combination planning. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： multi objective linear programming Environmental-life cycle assessment Life cycle cost Transit bus CO2 emission mitigation Air pollutant related health and environmental damage cost

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linear programming with Triangular Fuzzy Numbers-A Case Study in a Finance and Credit Institute

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FUZZY INFORMATION AND ENGINEERING 2013年第3期5卷 295-315页

作者： Nasseri, S. H. Behmanesh, E. Univ Mazandaran Dept Math Babol Sar Iran

The objective of this paper is to deal with a kind of fuzzy linear programming problem involving triangular fuzzy numbers. Then some interesting and fundamental results are achieved which in turn lead to a solution of fuzzy linear programming models without converting the problems to the crisp linear programming models. Finally, the theoretical results are also supported by a real case study in a banking system. The same idea is emphasized to be also useful when a general LR fuzzy numbers is given.

关键词： Fuzzy linear programming Fuzzy ordering multi objective linear programming Pareto optimal solution Triangular fuzzy numbers

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A modified method for constructing efficient solutions structure of MOLP

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APPLIED MATHEMATICAL MODELLING 2009年第5期33卷 2403-2410页

作者： Foroughi, A. A. Jafari, Y. Univ Qom Dept Math Qom 37165 Iran

This paper deals with a recently proposed algorithm for obtaining all weak efficient and efficient solutions in a multi objective linear programming (MOLP) problem. The algorithm is based on solving some weighted sum problems, and presents an easy and clear solution structure. We first present an example to show that the algorithm may fail when at least one of these weighted sum problems has not a finite optimal solution. Then, the algorithm is modified to overcome this problem. The modified algorithm determines whether an efficient solution exists for a given MOLP and generates the solution set correctly (if exists) without any change in the complexity. (c) 2008 Elsevier Inc. All rights reserved.

关键词： multi objective linear programming Efficient solutions set Solution structure

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