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4th International Conference on Industrial Engineering and Applications (ICIEA)

作者： Fatrias, Dicky Alfadhlani Kamil, Insannul Univ Andalas Dept Ind Engn Padang Indonesia

ISBN: (纸本)9781509067756

An increasing need to improve efficiency have been enforcing buyer companies to give more attention on their supplier. As one critical task within the company's supply chain management system, a proper supplier selection mechanism not only results in a more reliable and long term supplier-buyer partnership, but also provides opportunities to reduce various costs and realizes stable production. However, one of the main characteristic of supplier selection problem is that a fuzziness often adheres in the process of selection. In this paper, multi-objective-objective supplier selection problem is studied, and a grey fuzzy programming approach is developed to tackle uncertainty in decision maker's aspirations for fuzzy objectives, and in membership parameters of fuzzy objectives simultenously. In the formulated problem, uncertainty in the membership parameters is treated as interval grey numbers. A numerical example demonstrates our approach in providing a range of compromise solutions which impart more flexibility in supplier selection decisions.

关键词： supplier selection multi-objective problem fuzzy programming grey number

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New ranking function for fuzzy linear programming problem and system of linear equations

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JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES 2019年第1期40卷 141-156页

作者： Suneela, S. Chakraverty, S. Natl Inst Technol Rourkela Dept Math Rourkela 769008 Odisha India

Linear programming problems and System of Linear equations have many applications in various science and engineering problems like network analysis, operations research etc. In general Linear programming Problem (LPP) and the system of linear equations contain crisp parameters that is real numbers or complex numbers as their coefficients and constants, but in real life applications, LPP and system of equations may contain the constrains or the parameters as uncertain. These uncertain values are not the exact real numbers but vary within some range of values, the values may vary within an interval or can be considered as fuzzy *** this paper, we have developed a new Ranking function (which converts the fuzzy number into crisp) to solve a fully fuzzy LPP and System of equations. Unlike the previous ranking functions, the proposed ranking function uses fuzzy number itself improving the accuracy of the solution. The ranking function is derived by replacing the non-parallel sides of the trapezoidal fuzzy number with non-linear functions. Various numerical examples are included and compared with the pre-existing methods.

关键词： fuzzy Set Theory fuzzy programming System of equations Linear programming

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A fuzzy Quadratic programming Model for the Design Optimization of a Hybrid Renewable Energy-Water System for Tropical Buildings 10

A Fuzzy Quadratic Programming Model for the Design Optimizat...

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10th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Del Rosario, Aaron Jules R. Ubando, Aristotle T. Culaba, Alvin B. De La Salle Univ Mech Engn Dept Manila Philippines

ISBN: (纸本)9781538677674

The growing global energy demand and continuous dependency on fossil fuels have triggered concerns over energy security and global warming. This issue has led to the prioritization of renewable sources in order to achieve sustainable development in the energy sector. The use of hybrid renewable sources and polygeneration systems to develop a sustainable energy system have also been emphasized in the literature. Thus, this study aims to optimize the design of a hybrid renewable energy-water system for tropical buildings. A fuzzy quadratic programming model was developed from a system architecture utilizing solar and biomass sources to meet electricity, cooling, heating, and water demands. The objective is to maximize the degree of satisfaction, which is based on multiple objectives of meeting the projected demand and minimizing the economic and environmental impacts. Technical, economic, and environmental constraints are included in the model based on fuzzy membership functions. The model was demonstrated using a case study considering a tropical commercial hotel building. The optimized system design yields a degree of satisfaction of 0.9999, compared to 0.1351 for a system with solar energy as the only source. These results highlight the benefit of renewable source hybridization and polygeneration to design a sustainable energy system.

关键词： design optimization fuzzy programming polygeneration renewable energy tropical buildings

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fuzzy arithmetic on LR fuzzy numbers with applications to fuzzy programming

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JOURNAL OF INTELLIGENT & fuzzy SYSTEMS 2016年第1期30卷 71-87页

作者： Zhou, Jian Yang, Fan Wang, Ke Shanghai Univ Sch Management Shanghai 200444 Peoples R China

In practice, some special LR fuzzy numbers, like the triangular fuzzy number, the Gaussian fuzzy number and the Cauchy fuzzy number, are widely used in many areas to deal with various vague information. With regard to these special LR fuzzy numbers, called regular LR fuzzy numbers in this paper, an operational law is proposed for fuzzy arithmetic, providing a novel approach to analytically and exactly calculating the inverse credibility distribution of some specific arithmetical operations based on the credibility measure. As an application of the operational law, an equivalent form of the expected value operator as well as a theorem for computing the expected value of strictly monotone functions is suggested. Finally, we utilize the operational law to construct a solution framework of fuzzy programming with parameters of regular LR fuzzy numbers, and such type of fuzzy programming problems can be handled by the operational law as the classic deterministic programming without any particular solving techniques.

关键词： LR fuzzy number regular LR fuzzy number fuzzy arithmetic operational law expected value fuzzy programming

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Allocating emergency resource for leakage of dangerous chemicals at sea by fuzzy programming

Allocating emergency resource for leakage of dangerous chemi...

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第二届经济与企业管理国际学术会议

作者： Bin Wang Hao Hao College of International Vocational Education Shanghai Polytechnic University

In this study, we propose a fuzzy programming model that considers a single accident site and multiple emergency rescue bases. Various resource constraints, such as volume and weight capacity at the emergency rescue bases, are considered. Rescue funding availability is also integrated into the model. The results from a numerical example show that the model is mathematically valid and practically feasible. The proposed model can be used to provide insightful decision support information to liquid chemical leakage rescue effort.

关键词： emergency resources allocation emergency bases liquid bulk chemicals leakage accident fuzzy programming

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Multi-choice stochastic bi-level programming problem in cooperative nature via fuzzy programming approach

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Journal of Industrial Engineering International 2016年第3期12卷 287-298页

作者： Maiti, Sumit Kumar Roy, Sankar Kumar School of Applied Sciences and Humanities Haldia Institute of Technology Purba Midnapore Haldia 721 157 India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721 102 India

In this paper, a Multi-Choice Stochastic Bi-Level programming Problem (MCSBLPP) is considered where all the parameters of constraints are followed by normal distribution. The cost coefficients of the objective functions are multi-choice types. At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach. Further, a general transformation technique with the help of binary variables is used to transform the multi-choice type cost coefficients of the objective functions of Decision Makers(DMs). Then the transformed problem is considered as a deterministic multi-choice bi-level programming problem. Finally, a numerical example is presented to illustrate the usefulness of the paper. © 2016, The Author(s).

关键词： Bi-level programming fuzzy programming Multi-choice programming Non-linear programming Stochastic programming

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A note on optimum allocation for multiobjective sample surveys using fuzzy programming

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Journal of Survey Statistics and Methodology 2016年第2期4卷 171-187页

作者： Swain, A.K.P.C. Utkal University Bhubaneswar India

In sample surveys using stratified random sampling, the determination of optimum strata sample sizes is a well-known design requirement. When only one variable is relevant, the determination of the sample sizes is simple. However, when more than one variable is relevant, the optimum allocation problem gets complicated because an allocation that is optimum for one may not be optimum for others. Thus, we require a procedure to obtain a compromise allocation that is optimum in some sense for all of the variables or objectives under consideration. In this context, the sampling theory literature contains alternative methods to arrive at a compromise allocation in the face of multiple objectives. In this paper, a procedure based on multiobjective decision making using the fuzzy programming technique is proposed when either the total sample size or total cost of the survey is fixed. Numerical illustrations are provided to compare the proposed compromise allocation with some existing ones for single-stage stratified random sampling, two-stage sampling, and two-phase sampling. It is observed that the proposed compromise allocation results in a higher degree of compromise among the multiple objectives. © The Author 2016. Published by Oxford University Press on behalf of the American Association for Public Opinion Research. All rights reserved.

关键词： Compromise allocation fuzzy programming Multiple objectives Optimum allocation Stratified random sampling

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Multi-objective bilevel fuzzy probabilistic programming problem

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OPSEARCH 2017年第3期54卷 475-504页

作者： Ranarahu, N. Dash, J. K. Acharya, S. Siksha O Anusandhan Univ Inst Tech Educ & Res Dept Math Khandagiri Sq Bhubaneswar 751030 Odisha India KIIT Univ Sch Appl Sci Dept Math Bhubaneswar Orissa India

This paper presents an efficient method for solving a multi objective bilevel programming problem with multiple number of objective functions in both first level as well as in second level. The uncertain parameters are present in second level in form of fuzzy random variables. In this case the fuzzy random variables are assumed to be fuzzy normal random variables. First the fuzziness is removed by using alpha cut technique and randomness is removed by chance constrained method. Then multi objective bilevel programming problem is transformed into a single objective non-linear mathematical model by using fuzzy programming technique. This non-linear mathematical model is solved by existing methodology or software. A numerical example is presented to illustrate the efficiency and feasibility of the proposed method.

关键词： Stochastic programming Multi-objective programming fuzzy programming fuzzy normal random variables Bilevel programming Optimization techniques

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A fuzzy approach for the intuitionistic multi-objective linear fractional programming problem using a bisection method

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2025年第2期49卷 1-24页

作者： Kara, Nurdan Kocken, Hale Gonce Akdemir, Hande Gunay Natl Def Univ TR-34334 Istanbul Turkiye Yildiz Tech Univ Dept Math Engn TR-34220 Istanbul Turkiye Giresun Univ Dept Math TR-28200 Giresun Turkiye

In this paper, intuitionistic fuzzy multi-objective linear fractional programming problems (IFMOLFPs) with several fractional criteria, including profit/cost, profit/time, or profitability ratio maximization, are considered. Moreover, all parameters, with the exception of the decision variables, are characterized as triangular intuitionistic fuzzy numbers. The component-wise optimization method is employed to transform IFMOLFP into an equivalent crisp multi-objective linear fractional problem. Then, we use an iterative fuzzy methodology that integrates linear programming with a bisection approach. The proposed approach addresses single-objective and real-life multi-objective organizational planning problems, which are approached using various methods in the literature. It is used for non-linear membership functions in solving these problems. Furthermore, the values obtained using the ranking function are compared. Ultimately, the decision-maker selects the most appropriate solution technique based on the weights of the objective functions.

关键词： Multi-objective linear programming Fractional programming fuzzy programming Intuitionistic fuzzy number Bisection method Membership function

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A new fuzzy programming method to derive the priority vector from an interval reciprocal comparison matrix

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INFORMATION SCIENCES 2015年 316卷 148-162页

作者： Chen, Liuhao Xu, Zeshui PLA Univ Sci & Technol Coll Commun Engn Nanjing 210007 Jiangsu Peoples R China Sichuan Univ Sch Business Chengdu 610064 Peoples R China

In this paper, we discuss the interval reciprocal comparison matrices and suggest a new fuzzy programming method (NFPM) to derive the priority vector from an interval reciprocal comparison matrix. Based on Mikhailov's membership function, we first give a membership function, which is used to measure the decision maker's satisfaction degree for the priority vector derived from each interval constraint. Then by using the membership function, we propose a new fuzzy programming method to get the most satisfaction degree of each priority vector. The NFPM has many prominent characteristics, especially, it is capable of deriving the priority vector from a consistent or inconsistent interval reciprocal comparison matrix. Moreover, the NFPM can overcome some drawbacks of Mikhailov's fuzzy programming method (FPM) for inconsistent interval reciprocal comparison matrices. Finally, several examples are given to illustrate the applicability and advantage of the proposed method. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Interval reciprocal comparison matrix Inconsistent interval reciprocal comparison matrix fuzzy programming Priority vector

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