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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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Optimal Capacitor Allocation based on fuzzy Inference and fuzzy multi-objective programming in Distribution Network

Optimal Capacitor Allocation based on Fuzzy Inference and Fu...

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International Conference on Energy, Environment and Sustainable Development (ICEESD 2011)

作者： Wang Wei Zhang Jiliang Li Baoyin Shandong Sci & Technol Univ Sch Machine & Elect Engn Tai An 271019 Shandong Peoples R China

ISBN: (纸本)9783037852668

This paper presents an algorithm using a stepwise programming method to determine the suitable locations for capacitors installations and their ratings in distribution networks. The Voltage and loss reduction capability of nodes are regarded as input indices. The fuzzy inference method is used to obtain capacitor placement suitability of every node. The node having the highest suitability is selected as the compensation node. The energy losses of three time periods and the peak charge are modeled as optimization objective. fuzzy multi-objective programming is used to determine the proper sizes of the capacitors. Considering the each capacitor rating interaction, the circulation calculation method is used to recalculate the capacitor rating for compensated nodes. The results of test system demonstrate the effectiveness and practicability of the method.

关键词： distribution network capacitor allocation fuzzy inference fuzzy multi-objective programming

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Active Portfolio Management from a fuzzy multi-objective programming Perspective

Active Portfolio Management from a Fuzzy Multi-objective Pro...

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Evo Applications 2010 Conference

作者： Thomaidis, Nikos S. Univ Aegean Management & Engn Lab Dept Financial & Management Engn GR-82100 Chios Greece

ISBN: (纸本)9783642122415

We consider the problem of structuring a portfolio that outperforms a benchmark index, assuming restrictions on the total number of tradable assets. We experiment with non-standard formulations of active portfolio management, outside the mean-variance framework, incorporating approximate (fuzzy) investment targets and portfolio constraints. To deal with the inherent computational difficulties of cardinality-constrained active allocation problems, we apply three nature-inspired optimisation procedures: simulated annealing, genetic algorithms and particle swarm optimisation. Optimal portfolios derived from these methods are bench-marked against the Dow Jones Industrial Average index and two simpler heuristics for detecting good asset combinations, based on Monte-Carlo simulation and fundamental analysis.

关键词： Active portfolio management fuzzy multi-objective programming Cardinality constraints Evolutionary computation Simulated annealing Genetic algorithms Particle swarm optimisation

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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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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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fuzzy multi-objective linear programming approach for optimising a closed-loop supply chain network

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2013年第8期51卷 2443-2461页

作者： Ozceylan, Eren Paksoy, Turan Selcuk Univ Dept Ind Engn Konya Turkey

With the urgency of remanufacturing and environmental concerns, closed-loop supply chain (CLSC) networks have drawn the attention of researchers. Although there are many CLSC network models in the literature, most of them do not consider uncertainty in general terms. However, practical situations are often not well defined and thus cannot be described precisely in real world CLSCs. In this paper a mixed integer fuzzy mathematical model is proposed for a CLSC network which includes both forward and reverse flows with multiple periods and multiple parts. A fuzzy multi-objective model (FMOM) approach is applied to take into account the fuzziness in the capacity, objectives, demand constraints and also in the reverse rates. Computational results are presented for a number of scenarios to show and validate applicability and flexibility of the model. Results show that the proposed model presents a systematic framework which enables the logistics manager (LM) to adjust the search direction during the solution procedure to obtain a desired satisfactory solution.

关键词： closed-loop supply chain fuzzy multi-objective programming mixed integer linear programming multi-period

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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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Genetic Algorithm Based fuzzy multi-objective Nonlinear programming of Regional Water Allocation

Genetic Algorithm Based Fuzzy Multi-objective Nonlinear Prog...

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IEEE International Conference on Cybernetic Intelligent Systems (CIS 2008)

作者： Li Shurong Wang Feng Ma Tao Yan Wei China Univ Petr Coll Informat & Control Engn Dongying Peoples R China

ISBN: (纸本)9781424416738

A genetic algorithm (CA) based approach to solve a fuzzy multi-objective nonlinear programming (FMNP) problem is presented and applied to water resources allocation. A FMNP model of regional water allocation is established originally. The objective functions of the model include three conflicting goals which are economic profits, environment goal and society goal. By turning the FMNP to an optimal level cut problem, the "fuzzy optimal solution" is solved by using a genetic algorithm. An example of the Dongying's water allocation strategy is provided by using the proposed method.

关键词： fuzzy multi-objective programming fuzzy optimal solution water resource optimal allocation genetic algorithm

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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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Genetic algorithm-based fuzzy multi-objective programming approach to optimal allocation of environmental water requirements in rivers

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Gaojishu Tongxin/Chinese High Technology Letters 2006年第10期16卷 1077-1081页

作者： Yang, Wei Sun, Dezhi School of Municipal and Environmental Engineering Harbin Institute of Technology Harbin 150090 China

A fuzzy multi-objective-programming model was presented to determine appropriate environmental flow allocation for polluted urban rivers, in which the objectives included the maximization of assimilative capacity in the river, the minimization of water amount for allocation and the minimization of cost for water allocation. An integrated nonlinear fuzzy membership function, which represents a broader implication in fuzzy decision-making, was regarded as the general objective and the genetic algorithm became an essential tool in search for the global optimal solution. A case study of optimal allocation for environmental water requirements in the Liming River Basin and Daqing City demonstrates the capability of the fuzzy multi-objective model based on fuzzy decision theories to work suitably in water environmental management in a river basin.

关键词： Environmental water requirements Flow allocation fuzzy multi-objective programming Genetic algorithm

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