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Forest biomass-to-biofuel factory location problem with multiple objectives considering environmental uncertainties and social enterprises

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JOURNAL OF CLEANER PRODUCTION 2020年 262卷 121327-121327页

作者： Lin, Chun-Cheng Kang, Jia-Rong Huang, Guan-Lin Liu, Wan-Yu Natl Chiao Tung Univ Dept Ind Engn & Management Hsinchu 300 Taiwan Asia Univ Dept Business Adm Taichung 413 Taiwan China Med Univ China Med Univ Hosp Dept Med Res Taichung 404 Taiwan Tatung Univ Dept Informat Management Taipei 104 Taiwan Natl Chung Hsing Univ Dept Forestry Taichung 402 Taiwan Natl Chung Hsing Univ Innovat & Dev Ctr Sustainable Agr Taichung 402 Taiwan

Forest biomass energy enjoys merit of large production, renewability, and clean combustion. However, most related works focused on only the objective of minimization of cost or pollution, but seldom on the social aspect. Social enterprise provides business models that cope with social or environmental problems, e.g., offering employment opportunities in disadvantaged areas. Therefore, this work considers social enterprises and environmental uncertainties in a forest biomass-to-biofuel factory location problem with multiple objectives, which determines whether to open forest biomass-to-biofuel factories at their potential locations to meet the energy demand and other practical constraints. Aside from minimization of cost and carbon emissions, the concerned problem additionally considers the objective of maximizing the job offers provided by opening factories from the social enterprise aspect. Additionally, based on the fuzzy theory, this problem includes the following environmental uncertainties: uncertain number of inventory days, uncertain job offers per unit of surplus factory scale, uncertain biomass production amount, and uncertain biofuel demand due to the price fluctuation of fossil fuels. This work employs the GIS to determine candidate locations of acquiring forest biomass and opening factories, and then solves the problem by fuzzy multi-objective linear programming. Through simulation, we observe the conflict among objectives, compare the differences between the proposed method and previous methods, and analyze the key factors that affect practical implementation. Simulation results show that when the total biofuel demand exceeds 200 million liters per year, the proposed method provides 16% more job offers than the previous method that focused on only cost minimization. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Facility location problem Biomass-to-biofuel factory Social enterprise Sustainability fuzzy multi-objective linear programming fuzzy theory

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Optimization of remanufacturing systems by using a fuzzy multi-objective model to solve the planning problem

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JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES 2019年第4期40卷 853-881页

作者： Su, T. S. Wu, C. C. Lin, L. T. 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

To meet specific customer demands, many new materials and recyclable components must be mixed into the production process in order to minimize total manufacturing costs and total lead time. The lot-sizing production-to-order problem requires optimizing the lot size in the purchase and manufacture of required materials. This paper analyzes the relationships between new materials and recycled components with a specific purchase/ manufacturing cost, machine yield and capacity, and lead time. fuzzy multi-objective linear programming (FMOLP) is used to model relative cost-effectiveness and lead time, among various factors. The proposed model evaluates cost-effectiveness and lead time while integrating multiple products, multiple suppliers, multiple components and multiple machines for a remanufacturing production system. Decision makers and managers can use the analytical results of this work to improve their understanding of cost-effectiveness and lead time of recyclable remanufacturing planning.

关键词： Remanufacturing systems fuzzy multi-objective linear programming multiple products Lot-sizing

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Evaluation of trapezoidal fuzzy numbers on AHP based solution of multi-objective programming problems

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JOURNAL OF INTELLIGENT & fuzzy SYSTEMS 2016年第3期31卷 1869-1879页

作者： Akbas, Serkan Dalkilic, Turkan Erbay Karadeniz Tech Univ Fac Sci Dept Stat & Comp Sci TR-61080 Trabzon Turkey

multi-criteria decision making method is used in such cases having multiple targets. multi-objective linear programming problems, which deal with uncertain measurements for both objectives and constraints, are solved by fuzzy multi-objective linear programming methods. Analytic hierarchy process (AHP), one of the multi-criteria decision-making methods based on weighting of objectives, is designed to solve complex problems. In this study, multiple criteria decision making problems and decision makers' opinions on these problems as well as their solution processes are discussed. Firstly, a fuzzy multi objective linear programming problem is solved using the approaches of Zimmerman and Hybrid. In the literature, these methods are applied using triangular fuzzy numbers based on decision makers' opinions only in cases where the objective function is minimization. In this study, as an alternative to the triangular fuzzy numbers, trapezoidal fuzzy numbers are defined, and both minimization and maximization of objective functions are examined. Finally, a solution algorithm for a fuzzy multi-objective linear programming problem is proposed under some given conditions. The algorithm is applied to a sample problem that involves modeling of a congress organizing which aims to place attendees to accommodations under specific objectives and constraints. In the evaluation phase of the algorithm, targets are weighted by using triangular and trapezoidal fuzzy numbers. At the end, the results of the proposed algorithm are compared with the results of other methods in the literature.

关键词： Analytic hierarchy process fuzzy multi-objective linear programming trapezoidal fuzzy numbers

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A New Approach for Solving fuzzy Supplier Selection Problems Under Volume Discount

A New Approach for Solving Fuzzy Supplier Selection Problems...

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Academic Conference on 30th Anniversary of fuzzy Geometric programming and 40th Education Year by and of Cao Bingyuan (ACFGPAEC)

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

ISBN: (纸本)9783319665146;9783319665139

In order to achieve a compromised solution for a multi-objective linear programming with fuzzy right hand sides, Tchebycheff norm and a new approach based on alpha-cut is suggested to minimize the distance from the current estimate of the objective values from the ideal point. Since the obtained solutions by the Tchebycheff approach are weakly efficient for multi-objective problems. Hence, an augmented weighted Tchebycheff norm has been proposed. Here, the satisficing tradeoff algorithm is used to solve the augmented weighted Tchebycheff problems. Since the supplier selection problem is usually a multi-objective problem, the augmented weighted Tchebycheff method is applied for obtaining its solutions.

关键词： fuzzy multi-objective linear programming Augmented weighted Tchebycheff norm alpha-cut approach Satisficing tradeoff algorithm

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An Enhanced Two-phase Approach for fuzzy multi-objective linear programming in Supplier Selection Problem

An Enhanced Two-phase Approach for Fuzzy Multi-objective Lin...

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The Twelfth Asia Pacific Industrial Engineering ＆ Management Systems Conference(APIEMS 2011)

作者： Dicky Fatrias Yoshiaki Shimizu Department of Electronic and Information Engineering Toyohashi University of Technology 1-1 Hibarigaoka Tempaku-choToyohashi-shiAichi 441-8150Japan

Supplier selection is an essential task within the purchasing function of supply chain management because it provides companies with opportunities to reduce various costs and realize stable and reliable ***, many companies find it difficult to determine which suppliers should be targeted as they have varied strengths and weaknesses in performance which require careful screening by the ***,information required to assess every supplier is not known precisely and typically fuzzy in *** this paper,therefore,we present fuzzy multi-objective linear programming(FMOLP) with three important goals:cost minimization,service level maximization and purchasing risk minimization with some practical constraint such as suppliers' capacity,buyer's financial budget,*** solve the problem,we introduce an enhanced two-phase approach of fuzzy linear programming for the supplier *** the first phase,the minimum achievement level desired by decision maker is set to the solution from max-min operator *** the second phase,problem formulation is reconstructed to improve the minimum achievement level resulted from the first phase. For this purpose,additional term is introduced into the objective function to adjust the achievement level and the issue of infeasibility of ***,by varying the weighting factor,we provide a set of alternative solution which enables decision maker(DM) to select the best compromise solution based on his/her preferences. Numerical experiment is provided to demonstrate our *** programming in Supplier Selection Problem.

关键词： supplier selection fuzzy multi-objective linear programming supply chain

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Optimized Daily Diet Composition for a Nutritionally Balanced Diet: An Application of fuzzy multiple objective linear programming

Optimized Daily Diet Composition for a Nutritionally Balance...

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IEEE International Conference on fuzzy Systems (FUZZ-IEEE) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Tom, Mary Wibovo, Santoso Williams, Susan Cent Queensland Univ Sch Engn & Technol Brisbane Qld Australia Cent Queensland Univ Sch Engn & Technol Melbourne Vic Australia Cent Queensland Univ Sch Med & Appl Sci Rockhampton Qld Australia

ISBN: (纸本)9781509006250

Nutrition related diseases such as Cardiovascular Diseases, type 2 diabetes, and certain types of cancers are widely prevalent, and increasing in both developed and developing countries. This escalates the need to consistently follow a nutritionally balanced diet. Formulation of nutritionally balanced Meals is a complex task, which requires considerable effort, time, and intellectual capability for evaluation of Menu items and analysis of a range of nutrient values. As a step towards automating this task, this interdisciplinary study presents a fuzzy optimization model applying fuzzy multi-objective linear programming (FMOLP) to compose a daily diet consisting of nutritionally balanced Meals which limit nutrients such as cholesterol, sugar, saturated fat, and sodium. An effective algorithm is developed to create a pareto optimal solution set of optimized daily diet choices. The model is tested using one hundred Menu items, for demonstrating the applicability of the model in composing a nutritionally balanced diet.

关键词： Nutritionally balanced diet fuzzy optimization multi-objective decision making fuzzy multi-objective linear programming

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The use of a fuzzy multi-objective linear programming for solving a multi-objective single-machine scheduling problem

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APPLIED SOFT COMPUTING 2010年第3期10卷 919-925页

作者： Tavakkoli-Moghaddam, Reza Javadi, Babak Jolai, Fariborz Ghodratnama, Ali Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

This paper develops a fuzzy multi-objective linear programming (FMOLP) model for solving a multi-objective single-machine scheduling problem. The proposed model attempts to minimize the total weighted tardiness and makespan simultaneously. In this problem, a proposed FMOLP method is applied with respect to the overall acceptable degree of the decision maker (DM) satisfaction. A number of numerical examples are solved to show the effectiveness of the proposed approach. The related results are compared with the Wang and Liang's approach. These computational results show that the proposed FMOLP model achieves lower objective functions and higher satisfaction degrees. (C) 2009 Elsevier B. V. All rights reserved.

关键词： Single-machine scheduling multi-objective linear programming fuzzy multi-objective linear programming Decision maker

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Performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry

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JOURNAL OF CLEANER PRODUCTION 2015年第1期87卷 391-413页

作者： Jakhar, Suresh Kumar Indian Inst Management Rohtak Fac Operat Management Area Rohtak Haryana India

There is a growing concern that business enterprises and their supply chains focus primarily on economic activities and ignore their impact on the environment and society. This paper aims to help decision makers, managers, and practitioners to achieve economic growth, societal development, and environmental protection by developing sustainable supply chain performance measures and proposes a partner selection and flow allocation decision-making model. Survey data from 278 business organizations from the Indian apparel industry supply chain network were used, and an integrated method of structural equation modeling, fuzzy analytical hierarchy process, and fuzzy multi-objective linear programming was applied to the proposed model. The results of the structural equation modeling analysis indicate that the survey respondents considered sustainable production performance to be of prime importance, which thus indicates its significance in developing a sustainable supply chain for the apparel industry. To illustrate the use of the proposed model for partner selection and flow allocation decision making, real-time data from an apparel manufacturer are presented. Optimal results were obtained for two strategies sustainahility and cost saving-to show a cost-benefit trade-off when developing a sustainable supply chain. Using comparative performance, a decision maker can choose an appropriate strategy based on cost benefit analysis of the presented trade-offs. (C) 2014 Elsevier Ltd. All tights reserved.

关键词： Sustainable supply chain Performance measures Flow optimization Structural equation modeling fuzzy analytic hierarchy process fuzzy multi-objective linear programming

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fuzzy multi-objective procurement/production planning decision problems for recoverable manufacturing systems

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JOURNAL OF MANUFACTURING SYSTEMS 2015年第Part1期37卷 396-408页

作者： Su, Tai-Sheng Lin, Yu-Fan Natl Pingtung Univ Sci & Technol Dept Ind Management Pingtung 91201 Taiwan

In actual lot-sizing production-to-order problems for recoverable remanufacturing systems, input data or parameters are often imprecise or fuzzy. This study develops a novel fuzzy multi-objective linear programming (FMOLP) model with a piecewise linear merhbership function to solve integrated,procurement/production, planning decision problems with fuzzy environments and deal with multi-component, multi-vendor, multi-source and multi-machines under recoverable remanufacturing systems. The initial FMOLP model developed in this study attempts to simultaneously minimize total costs and total lead times in relation to supplier capacity, lead time, lot release, machine yield and customer demand. The proposed FMOLP model provides a systematic framework that facilitates a fuzzy decision-making process, enabling a decision maker to interactively adjust search direction during the solution procedure to obtain the preferred satisfactory solution. To test the model's adequacy, an actual implementation of several scenarios was conducted using remanufacturing production systems. The analytical results presented in this study can help decision managers better understand systematic analysis and the potential for improving cost-effectiveness and lead time in terms of recoverable remanufacturing planning. (C) 2014 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： Lot-sizing fuzzy multi-objective linear programming Recoverable remanufacturing systems Procurement/production planning

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Optimal vehicle-dispatch decisions for cement silos using a fuzzy multi-objective approach

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2014年第4期52卷 947-966页

作者： Su, Tai-Sheng Natl Pingtung Univ Sci & Technol Dept Ind Management Nei Pu Hsiang Pingtung Taiwan

In real dispatch problems for cement-silo trucks, input data or parameters, such as forecasting demand, resources, costs, and the objective function, are often imprecise or fuzzy because some information is incomplete, unavailable, or unobtainable. This work presents a novel fuzzy multi-objective linear programming (FMOLP) model that solves the cement-silo vehicle-dispatch problem in a fuzzy environment. This model is applied to solve multi-source, multi-product, multi-vehicle, and multi-ready-mixed-concrete (RMC) plant vehicle-dispatch problems with imprecise goals, input data, and parameters. This work elucidates the relationship between dispatch planning and RMC plants with a focus on the allocation of cement-silo trucks. This work uses a real cement study case to demonstrate the feasibility of the proposed model. The main contribution of this work is its fuzzy mathematical programming methodology for solving the cement-silo vehicle-dispatch problem in a fuzzy environment. The analytical results can help dispatchers analyse systematically the cost-effectiveness of vehicle-dispatch planning in practical applications.

关键词： cement silos vehicle dispatching problem fuzzy multi-objective linear programming

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