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A hybrid fuzzy approach for the closed-loop supply chain network design under uncertainty

JOURNAL OF INTELLIGENT & fuzzy SYSTEMS 2015年第6期28卷 2811-2826页

作者： Tavakkoli-Moghaddam, R. Sadri, S. Pourmohammad-Zia, N. Mohammadi, M. Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Res Ctr Org Proc Improvement Sari Iran

A closed-loop supply chain (CLSC) network consists of both forward and reverse supply chains. In this paper a CLSC network is investigated that involves four echelons in a forward direction including suppliers, manufacturer, distribution center and demand market, and three echelons in a backward direction including disposal, rework and collection centers. This paper presents a bi-objective model in order to design a network of bi-directional facilities in logistics network under uncertainties. Its objectives are to minimize the total costs as well as the total defective rate, disposal rate and pollution production rate. To solve the model, a hybrid solution approach is applied that combines fuzzy possibilistic programming and fuzzy multi-objective programming. Furthermore, in order to illustrate the validity of the model and applicability of the proposed solution approach, numerical experiments and the related sensitivity analysis are provided. Finally, the conclusion is provided.

关键词： Closed-loop supply chain fuzzy possibilistic programming fuzzy multi-objective programming uncertainty

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A Novel Hybrid Modelling for Aggregate Production Planning in a Reconfigurable Assembly Unit for Optoelectronics 22nd

A Novel Hybrid Modelling for Aggregate Production Planning i...

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22nd International Conference on Neural Information Processing (ICONIP)

作者： Sisca, Francesco G. Fiasche, Maurizio Taisch, Marco Politecn Milan Dept Management Econ & Ind Engn I-20133 Milan Italy

ISBN: (纸本)9783319265353;9783319265346

In this work it is presented a novel fuzzy multi-objective linear programming (FMOLP) model based on hybrid fuzzy inference systems for solving the general management framework fort the integration of a self-contained robotic reconfigurable assembly unit in a pre-existing shop-floor. It is developed an aggregate production planning in a fuzzy environment where the product price, unit inventory cost, unit assembly cost, resource-product suitability cost, availability of the assembly line, the assembly time and the 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 nominal capacity and inventory towards zero. Pareto solutions optimization is computed with different techniques and results are presented and discussed with interesting practical implications.

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

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multi-objective design of an organ transplant network under uncertainty

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2014年 72卷 101-124页

作者： Zahiri, B. Tavakkoli-Moghaddam, R. Mohammadi, M. Jula, P. Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Simon Fraser Univ Beedie Sch Business Burnaby BC V5A 1S6 Canada

We propose a novel multi-period location-allocation model for the design of an organ transplant transportation network under uncertainty. The model consists of a bi-objective mathematical programming model that minimizes total cost and time, including waiting time in the queue for the transplant operation, while considering organs' priorities. A fuzzy multi-objective programming based approach is presented to solve the small and medium size problems to optimality. For larger problems, we propose two meta-heuristics based algorithms. Lower bounds, and several numerical examples with managerial insights are discussed. A real case-study is provided, and the existing and the proposed optimal solutions are compared. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Healthcare network multi-period organ transplant network fuzzy multi-objective programming Queuing theory Meta-heuristics

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Predicting and optimization of energy consumption using system dynamics-fuzzy multiple objective programming in world heritage areas

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ENERGY 2013年第1期49卷 19-31页

作者： Wu, Zhibin Xu, Jiuping Sichuan Univ Uncertainty Decis Making Lab Chengdu 610064 Sichuan Peoples R China

Energy consumption and efficiency are important in regional low-carbon economic development and environmental protection. This paper provides a system dynamics and fuzzy multi-objective programming integrated approach for the prediction of energy consumption and CO2 emissions at a regional level. First, a general system dynamics model is constructed to analyze an economy-energy system. To deal with the uncertainties and optimize the parameters in the system, a fuzzy multiple objective programming model is used. This decision support model is then applied to predict the energy consumption of a world heritage area in China during 2010-2020. The results reveal that the energy consumption and CO2 emissions increase dramatically with rapid economic growth. In the scenario herein considered, which is based on the proposed optimization model, a 1932% reduction was found in the energy intensity decreases from 0.88 tce/10(4) RMB to 0.71 tce/10(4) RMB, and a 23.26% reduction in the CO2 emission intensity, from 2.15 t/10(4) RMB to 1.65 t/10(4) RMB. Policy suggestions such as adjusting the industrial structure, enhancing local hydro-power and renewable energy and increasing investment in energy technology and efficiency are indicated for the promotion of a low-carbon oriented economy in world heritage areas. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： System dynamics Energy consumption fuzzy multi-objective programming Industrial structure CO2 emissions

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Supply chain outsourcing risk using an integrated stochastic-fuzzy optimization approach

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INFORMATION SCIENCES 2013年 235卷 242-258页

作者： Wu, Dexiang Wu, Desheng Dash Zhang, Yidong Olson, David L. Univ Toronto Dept Mech & Ind Engn Toronto ON M5S 3G8 Canada Univ Toronto RiskLab Toronto ON M5S 3G8 Canada Univ Sci & Technol China Sch Management Hefei 230026 Anhui Peoples R China SUNY Buffalo Dept Ind & Syst Engn Buffalo NY 14260 USA Univ Nebraska Dept Management Lincoln NE 68588 USA

A stochastic fuzzy multi-objective programming model is developed for supply chain outsourcing risk management in presence of both random uncertainty and fuzzy uncertainty. Utility theory is proposed to treat stochastic data and fuzzy set theory is used to handle fuzzy data. An algorithm is designed to solve the proposed integrated model. The new model is solved using the proposed algorithm for a three stage supply chain example. Computation suggests an analysis of risk averse and procurement behavior, which indicates that a more risk-averse customer prefers to order less under uncertainty and risk. Trade-off game analysis yields supported points on the trade-off curve, which can help decision makers to identify proper weighting scheme where Pareto optimum is achieved to select preferred suppliers. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Supplier selection Supply chain risk management fuzzy multi-objective programming Utility

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Mixed model disassembly line balancing problem with fuzzy goals

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2013年第20期51卷 6082-6096页

作者： Paksoy, Turan Gungor, Askiner Ozceylan, Eren Hancilar, Arif Selcuk Univ Dept Ind Engn Konya Turkey Pamukkale Univ Dept Ind Engn Denizli Turkey

The collection of used products is the driving force of remanufacturing systems and enterprises can gain significant economic, technical and social benefits from recycling. All products are disassembled up to some level in remanufacturing systems. The best way to disassemble returned products is valid by a well-balanced disassembly line. In this paper, a mixed integer programming (MIP) model is proposed for a mixed model disassembly line balancing (MMDLB) problem with multiple conflicting objectives: (1) minimising the cycle time, (2) minimising the number of disassembly workstations and (3) providing balanced workload per workstation. In most real world MMDLB problems, the targeted goals of decision makers are frequently imprecise or fuzzy because some information may be incomplete and/or unavailable over the planning horizon. This study is the first in the literature to offer the binary fuzzy goal programming (BFGP) and the fuzzy multi-objective programming (FMOP) approaches for the MMDLB problem in order to take into account the vague aspirations of decision makers. An illustrative example based on two industrial products is presented to demonstrate the validity of the proposed models and to compare the performances of the BFGP and the FMOP approaches.

关键词： disassembly disassembly line balancing mixed model disassembly lines binary fuzzy goal programming fuzzy multi-objective programming mixed integer programming

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The fuzzy multi-objective programming Model and Solving Methods Based on Group Weight

The Fuzzy Multi-Objective Programming Model and Solving Meth...

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5th International Conference on fuzzy Systems and Knowledge Discovery

作者： Xiong, Guoqiang Pan, Quan Zhang, Hongcai Northwestern Polytech Univ Xian 710072 Peoples R China Xian Univ Technol Sch Business Adm Xian 710054 Peoples R China

ISBN: (纸本)9780769533056

This paper proposed an issue that among the objectives it need to weight to reflect the different importance in the fuzzy multi-objective programming. Established a fuzzy multi-objective programming model with preference weight;Taking into account many decision-makers participating in evaluation, gave a method which made the preference information set of different forms assembled into group preference, and applied integrated weight into the fuzzy multi-objective programming. Finally, examples are given in this paper to verify the effectiveness of the model and method.

关键词： fuzzy multi-objective programming group decision preference weight

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A web-based methodology for convergent product fuzzy networks using the Steiner tree

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JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2013年第7期30卷 415-432页

作者： Hassanzadeh, Reza Mahdavi, Iraj Mahdavi-Amiri, Nezam Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran Sharif Univ Technol Fac Math Sci Tehran Iran

An important manufacturing technology spectrum is to consider rapid and sensitive assemblies through convergent product (CP) in digital environment. We integrate functions and sub-functions using a comprehensive mathematical optimization process. To form the CP, a web-based fuzzy network is considered in which a collection of base functions and sub-functions configure the nodes and each arc in the network is to be a link between two nodes. The aim is to find an optimal tree of functionalities in the network adding value to the product in the web environment. First, a purification process is performed in the product network to assign the links among bases and sub-functions. Then, fuzzy numbers as benefits, costs and customers' value are determined. Next, the fuzzy Steiner tree methodology is adapted to a multi-objective model of the network to find the optimal tree determining the value adding sub-functions to bases in a CP. A new fuzzy multi-objective optimization is developed to work out the problem. Finally, an example is worked out to illustrate the proposed approach.

关键词： convergent product web-based (digital) network fuzzy multi-objective programming Steiner tree fuzzy number

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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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Bees Algorithm for constrained fuzzy multi-objective two-sided assembly line balancing problem

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OPTIMIZATION LETTERS 2012年第6期6卷 1039-1049页

作者： Tapkan, Pinar Ozbakir, Lale Baykasoglu, Adil Erciyes Univ Dept Ind Engn Kayseri Turkey Dokuz Eylul Univ Dept Ind Engn Izmir Turkey

Bees Algorithm is one of the swarm intelligence based heuristics which tries to model natural behaviour of honey bees in food foraging and used to solve optimization problems. On the other hand, Two-sided Assembly Line Balancing Problem is a generalization of simple Assembly Line Balancing Problem where different assembly tasks are carried out on the same product in parallel at both left and right sides of the line. Two-sided assembly lines are generally employed for the assembly of large-sized products such as buses and trucks. Furthermore, many real life problems contain imprecise objectives and fuzzy multi-objective programming gives an opportunity to handle such situations. In this study, Two-sided Assembly Line Balancing Problem is considered more realistically by employing positional, zoning and synchronous task constraints and by utilizing fuzzy approaches so as to maximize work slackness index and line efficiency, and minimize total balance delay. For solving this problem Bees Algorithm is used as a search mechanism for obtaining good solutions and extensive computational results are presented.

关键词： Bees Algorithm Two-sided assembly line balancing problem fuzzy multi-objective programming

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