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fuzzy multi-objective programming: A systematic literature review

EXPERT SYSTEMS WITH APPLICATIONS 2022年第0期196卷 116663-116663页

作者： Karimi, Negar Feylizadeh, Mohammad Reza Govindan, Kannan Bagherpour, Morteza Islamic Azad Univ Dept Ind Engn Shiraz Branch Shiraz Iran Shanghai Maritime Univ China Inst FTZ Supply Chain Shanghai 201306 Peoples R China Univ Southern Denmark Ctr Sustainable Supply Chain Engn Danish Inst Adv Study Dept Technol & Innovat Campusvej 55 Odense M Denmark Yonsei Univ Yonsei Frontier Lab Seoul South Korea Iran Univ Sci & Technol Dept Ind Engn Tehran Iran

multi-objective programming is commonly used in the literature when conflicted objectives arise in solving optimization problems. Over the past decades, classical optimization methods have been developed as useful tools to discover optimal solutions for multi-objective problems (MOPs). In recent years, under uncertainty, multi-objective Optimization (MOO) has received much attention due to its practical applications in real-world problems. However, many studies have been conducted on this matter. Some of which ignored the effects of uncertainty on optimization problems. This paper systematically reviews and summarizes various multi-objective methods applied to the problems with more than one objective in uncertain environments where uncertainty is expressed using fuzzy sets. In this paper, 439 articles on fuzzy multi-objective programming published from 1978 to 2021 are reviewed using corresponding texts, charts, and tables. Finally, the basic features of MOO are briefly presented, along with a prologue of MOO techniques and current trends. Recommendations for further research are also is provided.

关键词： fuzzy environment fuzzy multi-objective programming multi-objective optimization methods Asystematic literature review

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A fuzzy multi-objective programming model for the delivery and distribution of humanitarian relief materials

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 137卷

作者： Chai, Ruirui He, Hongwei Liu, Dehai Chen, Jingfeng North China Univ Water Resources & Elect Power Sch Management & Econ Zhengzhou 450046 Henan Peoples R China Dalian Univ Technol Inst Syst Engn Dalian 116024 Liaoning Peoples R China Dongbei Univ Finance & Econ Sch Publ Adm Dalian 116025 Liaoning Peoples R China Zhengzhou Univ Affiliated Hosp 1 Hlth Management Ctr Zhengzhou 450052 Peoples R China Zhengzhou Univ Intervent Inst Zhengzhou 450052 Henan Peoples R China

Disaster relief presents many unique logistics challenges, including damaged transportation infrastructure, multiple conflicting goals, and secondary disasters caused by spontaneous disaster relief. The delivery and distribution of humanitarian relief materials faced by nonprofit organizations (NPOs) poses a critical challenge due to the highly unpredictable nature of disasters, conflicting missions, and the need to navigate government regulations in disaster management. In this paper, we propose a novel multi-objective disaster relief modeling system for NPOs, considering (1) prioritization (providing medical services to seriously injured victims), (2) effectiveness (degree of satisfaction), (3) efficiency (operational costs), and (4) equity (cost of maintaining order). To incorporate the practical constraints of disaster relief operations, we include factors such as road damage, transportation capacity limitations, and route flow saturation as part of the model formulation. We then utilize fuzzy multi-objective programming to optimize the proposed disaster relief model, considering two relief distribution schemes: a common NPOs' spontaneous relief scheme and a newly designed traffic control scheme with government regulation. Based on the real-world scenario of the 2008 Wenchuan earthquake, we demonstrate that the designed traffic control scheme exhibited remarkable improvement among the NPOs' four objectives compared to the spontaneous relief scheme. Moreover, in the process of solving fuzzy multi-objective programming problems, artificial intelligence technology is employed to handle the fuzziness in multi-objective and automatically adjust parameters, making the solution results better and in line with practical situations. And we also validate the proposed model can be solved in polynomial time, meeting the engineering practice requirements, and can be easily extend to most disaster relief distribution scenarios.

关键词： Humanitarian logistics fuzzy multi-objective programming Disaster relief management Conflicting missions Traffic control

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Designing sustainable supply chain networks under uncertain environments: fuzzy multi-objective programming

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JOURNAL OF CLEANER PRODUCTION 2018年 174卷 1550-1565页

作者： Tsao, Yu-Chung Vo-Van Thanh Lu, Jye-Chyi Yu, Vincent Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei Taiwan Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA

Sustainable supply chain networks have attracted considerable attention in recent years as a means of dealing with a broad range of environmental and social issues. This paper reports a multi-objective mathematical programming model for use in the design of a sustainable supply chain network under uncertain conditions. The proposed model is aimed at maximizing social benefits while minimizing economic costs and environmental impacts. The objective assists in making decisions concerning the selection of production technologies and materials and determining the number and locations of production and distribution centers and the quantity of product to be transported between facilities. Uncertainty related to customer demand is dealt by using stochastic variables, whereas overall costs, carbon emissions, job opportunities, and the detrimental effects of the resulting solutions are handled using fuzzy numbers. An interactive method based on two-phase stochastic programming and fuzzy probabilistic multi-objective programing is used to overcome problems related to uncertainty. Finally, numerical analysis demonstrates the efficacy and efficiency of the proposed model. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Sustainable supply chain network multi-echelon Economic benefits Environmental and social responsibilities fuzzy multi-objective programming Two-phase stochastics programming

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A fuzzy multi-objective programming approach for determination of resilient supply portfolio under supply failure risks

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JOURNAL OF PURCHASING AND SUPPLY MANAGEMENT 2017年第3期23卷 211-220页

作者： Lee, Shyh-hwang Shu Te Univ Sci & Technol Grad Sch Business & Adm Kaohsiung Taiwan

The main contribution of this paper is to develop a new decision tool that interprets strategies for determination of resilient supply portfolio under supply failure risks. The strategic decisions include the allocation of emergency capacities to be pre-positioned at backup suppliers, the output of which can be increased in the event of mitigating a shortage caused by another supplier's failure. The model contains three objective functions minimising the total cost, minimising the net rejected items and minimising the net late deliveries while satisfying capacity and minimum order quantity requirement constraints. A weighted additive fuzzy multi objective model is proposed to simultaneously consider the imprecision of information and the relative importance of objectives for determining the allocation of order quantity and emergency capacity to each supplier. The application of the proposed model is illustrated using an example case of global supply chains with different supplier characteristics.

关键词： Resilient supply portfolio Supplier order allocation Supply failure risk Emergency capacity fuzzy multi-objective programming

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Applying fuzzy multi-objective linear programming to a project management decision with nonlinear fuzzy membership functions

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NEURAL COMPUTING & APPLICATIONS 2017年第8期28卷 2193-2206页

作者： Ehsani, Ehsan Kazemi, Nima Olugu, Ezutah Udoncy Grosse, Eric H. Schwindl, Kurt Islamic Azad Univ Young Researchers & Elite Club Sari Iran Univ Malaya Fac Engn Dept Mech Engn Ctr Prod Design & Mfg Kuala Lumpur 50603 Malaysia Tech Univ Darmstadt Inst Prod & Supply Chain Management Hsch Str 1 D-64289 Darmstadt Germany Univ Appl Sci Wurzburg Schweinfurt Dept Business & Ind Engn Ignaz Schon Str 11 D-97421 Schweinfurt Germany

This paper investigates a multi-objective project management problem where the goals of the decision maker are fuzzy. Prior research on this topic has considered linear membership functions to model uncertain project goals. Linear membership functions, however, are not much flexible to model uncertain information of projects in many situations, and therefore, fuzzy models with linear membership functions are not suitable to be applied in many practical situations. Hence, the purpose of this paper is to apply nonlinear membership functions in order to develop a better representation of fuzzy project planning in practice. This approach supports managers in examining different solution strategies and in planning projects more realistically. In doing so, a fuzzy mathematical project planning model with exponential fuzzy goals is developed first which takes account of (a) the time between events, (b) the crashing time for activities, and (c) the available budget. Following, a weighted max-min model is applied for solving the multi-objective project management problem. The performance of the developed solution procedure is compared with the literature that applied linear membership functions to this problem, and it is shown that the model developed in this paper outperforms the existing solution.

关键词： Project management Nonlinear fuzzy membership function Exponential membership function fuzzy multi-objective programming Weighted max-min approach

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Cost-effectiveness analysis of the mobile phone manufacturing sector by using a novel fuzzy multi-objective programming model

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SCIENTIA IRANICA 2016年第3期23卷 1370-1383页

作者： Su, T. S. Wu, C. C. Lin, C. H. Natl Pingtung Univ Sci & Technol Dept Ind Management 1 Hsueh Fu Rd Pingtung 912 Taiwan I SHOU Univ Dept Informat Management 1Sec 1Syuecheng Rd Kaohsiung 84001 Taiwan

This work presents a novel fuzzy multi-objective programming (FMOP) model with a modified S-curve membership function capable of solving integrated multi-component, multi-supplier, and multi-time-period production planning problems by using fuzzy objectives for the mobile phone manufacturing sector. The proposed model attempts to minimize total manufacturing, total inventory holding and total penalty costs simultaneously in relation to manufacturer/supplier capacity and warehouse space. Additionally, the proposed model provides a systematic means of facilitating the fuzzy decision-making process, enabling decision makers to interactively adjust the search direction during the solution procedure in order to obtain the preferred satisfactory solution of a decision maker (DM). Moreover, adequacy of the proposed model is demonstrated, based on an implementation design involving several scenarios of manufacturing production system for mobile phones. Analytical results provide a valuable reference for decision managers attempting to more thoroughly understand the systematic analysis and potential of cost-effective production planning. (C) 2016 Sharif University of Technology. All rights reserved.

关键词： Mobile phone fuzzy multi-objective programming S-curve membership function Costeffectiveness Production planning Manufacturer/supplier

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A Novel Hybrid fuzzy multi-objective Linear programming Method of Aggregate Production Planning

A Novel Hybrid Fuzzy Multi-objective Linear Programming Meth...

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25th International Workshop on Neural Networks (WIRN)

作者： Fiasche, Maurizio Ripamonti, Gaia Sisca, Francesco G. Taisch, Marco Tavola, Giacomo Politecn Milan Dept Management Econ & Ind Engn Milan Italy

ISBN: (纸本)9783319337470

In this work a novel fuzzy multi-objective linear programming (FMOLP) method based on hybrid fuzzy inference systems is proposed for solving the general framework of integration of self-contained assembly unit in a fuzzy environment where the product price, unit cost of not utilization of resources, work force level, production capacity and market demands are fuzzy in nature. The proposed model attempts to minimize total production costs, maximizing the shop floor resources utilization and the profits, considering inventory level, and capacity. Pareto solutions optimization is computed with different techniques and results are presented and discussed with interesting practical implications.

关键词： Aggregate production planning Hybrid fuzzy system APP fuzzy multi-objective programming

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A fuzzy multi-objective programming model for supplier selection with volume discount and risk criteria

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第5-8期71卷 1483-1492页

作者： Aghai, Shima Mollaverdi, Naser Sabbagh, Mohammad Saeed Tehran Payamnoor Univ TPNU Esfahan Iran Isfahan Univ Technol IUT Esfahan Iran

In contemporary supply chain management, the performance of potential suppliers is evaluated against multiple criteria. In this paper, a fuzzy multi-objective programming model is outlined to propose supplier selection taking quantitative, qualitative, and risk factors into consideration. Also quantity discount has been considered to determine the best suppliers and to place the optimal order quantities among them. The mixed integer derivative nonlinear programming is obtained from fuzzy multi-objective programming model by chance-constrained method. To solve this problem, an innovative method is proposed. In addition, several "what if" scenarios are facilitated. Finally, a real-life sample is used to validate the proposed model.

关键词： Supplier selection Risk fuzzy multi-objective programming Chance-constrained Discount quantity

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Cluster analysis for ethical portfolio optimization problem using fuzzy chance constrained programming

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ENVIRONMENTAL ECONOMICS AND POLICY STUDIES 2024年 1-22页

作者： Messaoudi, Laila Higher Inst Management Gabes Res Unit 3E Gabes Tunisia

Choosing the greatest investment possibilities to maximize the value of one's stock investment has always been one of the primary concerns of investors. However, issues like human rights, and business ethics, are at the forefront of the public and political conversation in today's world of globalization and interdependence. Many financial experts, policymakers, and economic and social researchers view Islamic finance as a potential solution to prevent future crises. Consequently, there is a need for new models to facilitate this investment approach. In this study, we propose a new hybrid approach to portfolio selection which combines multiple methodologies like investor topology, cluster analysis, preference modeling and fuzzy multi-objective programming strategy. The proposed model is applied on 9 Tunisian mutual funds including conventional and ethical/Islamic funds in Tunisian financial market. The findings reveal that higher expected losses and greater proportions of ethical or Islamic stocks in a portfolio translate into better portfolio performance as measured by the Sharpe ratio. These findings confirm our hypothesis that ethical investments should be taken into account when developing investment strategies for conventional investors.

关键词： Cluster analysis Preference modeling fuzzy multi-objective programming Ethical investment Islamic finance

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Textile supply chain management considering carbon emissions and apparel demand fuzziness: a fuzzy mathematical programming approach

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INTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY 2022年第2期34卷 137-155页

作者： Yaghin, R. Ghasemy Sarlak, P. Amirkabir Univ Technol Dept Text Engn Tehran Iran

Purpose This paper studies the textile supply chain tactical planning under demand fuzziness through considering environmentally friendly and social responsibility. Hence, carbon emission in textile production and transportation is considered along with supply chain profitability. Design/methodology/approach The authors present a fuzzy multi-objective mathematical optimization model with credibilistic chance constraints to determine the fabric procurement quantities and production plan under uncertainty. The solution procedure makes use of credibility measure and fuzzy aggregation operator to attain compromise solutions. Findings A trade-off among carbon emissions, social performance and supply chain total profit is conducted. The analyses indicate the importance of transportation costs and carbon emission while determining the supply chain's tactical plan. Originality/value The textile supply chain's social sustainability alongside carbon emissions of textile operations is contemplated to provide apparel production and distribution logistics planning under uncertainty. In doing so, the authors propose a hybrid credibility-possibility mathematical optimization model to determine a compromise solution for textile managers.

关键词： Textile production planning Environmental friendliness of textile supply chain fuzzy multi-objective programming Social responsibility

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