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fuzzy mathematical programming APPROACH FOR SOLVING fuzzy LINEAR FRACTIONAL programming PROBLEM

RAIRO-OPERATIONS RESEARCH 2014年第1期48卷 109-122页

作者： Veeramani, Chinnadurai Sumathi, Muthukumar PSG Coll Technol Dept Appl Math & Computat Sci Coimbatore Tamil Nadu India

In this paper, a solution procedure is proposed to solve fuzzy linear fractional programming (FLFP) problem where cost of the objective function, the resources and the technological coefficients are triangular fuzzy numbers. Here, the FLFP problem is transformed into an equivalent deterministic multi-objective linear fractional programming (MOLFP) problem. By using fuzzy mathematical programming approach transformed MOLFP problem is reduced single objective linear programming (LP) problem. The proposed procedure illustrated through a numerical example.

关键词： Triangular fuzzy number Linear programming problem multi objective linear fractional programming problem fuzzy mathematical programming

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fuzzy mathematical programming approach to heterogeneous multiattribute decision-making with interval-valued intuitionistic fuzzy truth degrees

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INFORMATION SCIENCES 2015年 325卷 484-503页

作者： Wan, Shu-Ping Li, Deng-Feng Fuzhou Univ Sch Econ & Management Fuzhou 350108 Fujian Peoples R China Jiangxi Univ Finance & Econ Coll Informat Technol Nanchang 330013 Peoples R China

Considering the hesitancy degrees on pair-wise comparisons of alternatives as interval-valued intuitionistic fuzzy (IVIF) sets (IVIFSs), we develop a new fuzzy mathematical programming method for solving heterogeneous multiattribute decision-making problems based on the Linear programming Technique for Multidimensional Analysis of Preference. In this method, IVIFSs, intuitionistic fuzzy sets (IFSs), trapezoidal fuzzy numbers, linguistic variables, intervals and real numbers are used to represent multiple types of attribute values and the attribute weights are not completely known. The preference relations between alternatives given by decision maker are expressed with IVIFSs of ordered pairs of alternatives. The consistency and inconsistency indices are defined as IVIFSs on the basis of comparisons of alternatives with IVIF truth degrees. The attribute weights and fuzzy ideal solution (FIS) are estimated through constructing a fuzzy mathematical programming model, which is solved by the technically developed method of IVIF mathematical programming. Hereby the distances of alternatives to the FIS are computed to rank the alternatives. Some generalization and discussion on the constructed IVIF mathematical programming model are also presented. A green supplier selection example is provided to illustrate the effectiveness of the proposed model and method. The comparison analyses verify the superiorities of the proposed method. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Multiattribute decision-making fuzzy mathematical programming Interval-valued intuitionistic fuzzy set Linear programming Technique for Multidimensional Analysis of Preference Green supply chain

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fuzzy mathematical programming and Self-Adaptive Artificial Fish Swarm Algorithm for Just-in-Time Energy-Aware Flow Shop Scheduling Problem With Outsourcing Option

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IEEE TRANSACTIONS ON fuzzy SYSTEMS 2020年第11期28卷 2772-2783页

作者： Tirkolaee, Erfan Babaee Goli, Alireza Weber, Gerhard-Wilhelm Mazandaran Univ Sci & Technol Dept Ind Engn Babol *** Iran Istinye Univ Dept Ind & Syst Engn TR-34010 Istanbul Turkey Univ Isfahan Fac Engn Esfahan *** Iran Poznan Univ Tech Fac Engn Management PL-60965 Poznan Poland Middle East Tech Univ Inst Appl Math TR-06800 Ankara Turkey

Flow shop scheduling (FSS) problem constitutes a major part of production planning in every manufacturing organization. It aims at determining the optimal sequence of processing jobs on available machines within a given customer order. In this article, a novel biobjective mixed-integer linear programming (MILP) model is proposed for FSS with an outsourcing option and just-in-time delivery in order to simultaneously minimize the total cost of the production system and total energy consumption. Each job is considered to be either scheduled in-house or to be outsourced to one of the possible subcontractors. To efficiently solve the problem, a hybrid technique is proposed based on an interactive fuzzy solution technique and a self-adaptive artificial fish swarm algorithm (SAAFSA). The proposedmodel is treated as a single objectiveMILP using a multiobjective fuzzy mathematical programming technique based on the e-constraint, and SAAFSA is then applied to provide Pareto optimal solutions. The obtained results demonstrate the usefulness of the suggested methodology and high efficiency of the algorithm in comparison with CPLEX solver in different problem instances. Finally, a sensitivity analysis is implemented on the main parameters to study the behavior of the objectives according to the real-world conditions.

关键词： Energy-conservation flow shop scheduling (FSS) fuzzy mathematical programming outsourcing option self-adaptive artificial fish swarm algorithm (SAAFSA)

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fuzzy mathematical programming applied to multi-level programming problems

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COMPUTERS & OPERATIONS RESEARCH 2003年第9期30卷 1259-1268页

作者： Sinha, S Indian Inst Technol Dept Math Kharagpur 721302 W Bengal India

An alternative multi-level programming technique based on fuzzy mathematical programming (FMP) is developed which gives better solutions than that proposed by Shih et al. (Comput. Oper. Res. 23(1) (1996) 73). The method uses the objectives in a sequential order of the hierarchy interactively and takes into account the desire of the DM at each stage. The technique is equally applicable to linear/nonlinear multi-level (say P levels) programming problems (MLPPs).

关键词： hierarchical systems fuzzy mathematical programming membership functions satisfactory solution

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fuzzy mathematical programming for traffic safety planning on an urban expressway

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Transportation Planning and Technology 1993年第2期17卷 179-179页

作者： Akiyama, Takamas Eu Shao, Chun Department of Transport Engineering Kyoto University Sakyo-ku Kyoto 606 Japan

Traffic safety planning has received increased attention because a number of accidents still occur on urban area transportation networks. The optimization approach, using budget constraints, is applicable to many problems of infrastructure planning that must be carried out under these circumstances. The problems of choosing which traffic safety facilities to construct on urban expressways are investigated in this study. This type of economic problem is formulated as an optimization of combinations problem. Incremental benefit‐cost analysis and Dynamic programming using fuzzy budget constraints are introduced. Particularly, the standard algorithm normally used to solve this problem is modified, because the fuzzy goal is defined as a step function in this type of problem. In addition, the shapes of the membership functions of fuzzy constraints are also discussed. The facts from a case study of the Hanshin Expressway (in the Kansai area of Japan) will be presented to illustrate how fuzzy theory improves the theoretical congruence with reality and adds robustness to actual traffic safety planning.

关键词： Traffic safety planning fuzzy mathematical programming fuzzy constraints

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fuzzy mathematical programming approaches for reverse supply chain optimization with disassembly line balancing problem

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JOURNAL OF INTELLIGENT & fuzzy SYSTEMS 2014年第4期26卷 1969-1985页

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

Today, the requirement of reverse supply chain (RSC) optimization takes more attention due to environmental and competitive factors. However, increasing attention and existing uncertainty in RSC also increases the difficulties for decisions of production/distribution planning. Therefore, considering strategic and tactical decisions together under fuzziness is being essential. This paper presents a fuzzy programming approach to the integration of RSC optimization (strategic level) and disassembly line balancing (DLB) (tactical level) problems. The aim of this study is to apply fuzzy modeling to optimize a RSC that involves customers, collection/disassembly centers and plants while balancing the disassembly lines in disassembly centers, simultaneously. Two types of fuzzy mathematical programming models with different aggregation operators are used. Finally, accuracy and applicability of the model is illustrated and a comparison of fuzzy approaches is done via a hypothetical example.

关键词： Disassembly line balancing fuzzy mathematical programming nonlinear mixed integer programming reverse supply chain

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fuzzy mathematical programming approach for Solving fuzzy Linear Fractional programming Problem

Fuzzy Mathematical programming approach for Solving Fuzzy Li...

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IEEE International Conference on fuzzy Systems (FUZZ)

作者： Veeramani, C. Sumathi, M. PSG Coll Technol Dept Appl Math & Computat Sci Coimbatore Tamil Nadu India

ISBN: (纸本)9781479900206

In this paper, a method is proposed to solve fuzzy Linear Fractional programming (FLFP) problem where cost of the objective function, the resources and the technological coefficients are triangular fuzzy numbers. Here, the FLFP problem is transformed into an equivalent deterministic Multi-Objective Linear Fractional programming (MOLFP) problem. By using fuzzy mathematical programming approach transformed MOLFP problem is reduced single objective Linear programming (LP) problem. The proposed procedure illustrated through a numerical example.

关键词： Triangular fuzzy number Linear programming problem Multi objective linear programming problem fuzzy mathematical programming

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Available-to-promise based bidding decision by fuzzy mathematical programming and genetic algorithm

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COMPUTERS & INDUSTRIAL ENGINEERING 2011年第4期61卷 993-1002页

作者： Cheng, Chi-Bin Cheng, Chao-Jung Tamkang Univ Dept Informat Management New Taipei City Taiwan Kun Shan Univ Dept Informat Engn Tainan Taiwan

The present study attempts to integrate bidding decisions with order promising and production planning to enhance supplier profitability and service level. This study formulates the bid price and production plan as a mixed integer programming model with fuzzy constraints. The fuzzy constraints represent the decision-maker's subjective judgment regarding the customer's price tolerance. The proposed model combines the advanced available-to-promise (AATP) concept to find optimum resource allocation and enable accurate estimations of production costs and delivery dates. The proposed solution procedure determines the optimum bid price by striking a compromise between profitability and the possibility to win the contract. This study develops a genetic algorithm to solve this problem, and provides computer simulated experiments to evaluate the performance of the proposed approach. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Reverse auction Bidding Advanced available-to-promise fuzzy mathematical programming Genetic algorithm

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Simultaneous allocation and data reconciliation procedure in life cycle inventory analysis using fuzzy mathematical programming

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ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING 2011年第5期6卷 794-800页

作者： Ilagan, Ethel R. Tan, Raymond R. De La Salle Univ Dept Chem Engn Manila 1004 Philippines

Life cycle assessment (LCA) is a methodology used in assessing the environmental impacts of products. Life cycle inventory analysis (LCI) is one of the four components of LCA which quantifies flows of materials and pollutants in the entire life cycle (cradle-to-grave) of the product. Data are commonly collected from various sources (e. g. publications, databases and site-specific measurements) which may result in violations of mass and energy balances due to uncertainties. In such cases, the data can be adjusted using reconciliation methods to improve the reliability of the results. Another computational issue in LCI arises when two or more products are involved, known as the multi-functionality or allocation problem. The problem is how to allocate resource and emission streams to each product. This work describes a model using fuzzy optimization for solving both allocation and data reconciliation problems simultaneously. The model is illustrated on an aluminum industry case study involving open-loop recycling, and the approach is compared with two sequential allocation and data reconciliation methods. (C) 2010 Curtin University of Technology and John Wiley & Sons, Ltd.

关键词： life cycle inventory analysis data reconciliation allocation fuzzy mathematical programming

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Environmental supply chain network design using multi-objective fuzzy mathematical programming

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APPLIED mathematical MODELLING 2012年第8期36卷 3433-3446页

作者： Pishvaee, Mir Saman Razmi, Jafar Univ Tehran Dept Ind Engn Coll Engn Tehran Iran

The concern about environmental impact of business activities has spurred an interest in designing environmentally conscious supply chains. This paper proposes a multi-objective fuzzy mathematical programming model for designing an environmental supply chain under inherent uncertainty of input data in such problem. The proposed model is able to consider the minimization of multiple environmental impacts beside the traditional cost minimization objective to make a fair balance between them. A life cycle assessment-based (LCA-based) method is applied to assess and quantify the environmental impact of different options for supply chain network configuration. Also, to solve the proposed multi-objective fuzzy optimization model, an interactive fuzzy solution approach is developed. A real industrial case is used to demonstrate the significance and applicability of the developed fuzzy optimization model as well as the usefulness of the proposed solution approach. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Environmental supply chain Supply chain network design Life cycle assessment fuzzy mathematical programming Multi-objective optimization

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