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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： SHENG-HUA WANG QUN-FENG ZHANG Department of Applied Mathematics North China Electric Power University Baoding 071003 China College of Mathematics and Computer Science Hebei University Baoding 071002China

Based on credibility theory, this paper presents a new class of fuzzy programming-quadratic fuzzy programming with recourse problem. Some basic properties of the model are discussed. In order to solve the model, a heuristic solution method, which combines fuzzy simulations, neural network and tabu search algorithm, is designed. Finally, a numerical example is solved to show the effectiveness and the feasibility of the hybrid algorithm.

关键词： fuzzy programming Quadratic fuzzy programming Tabu search algorithm fuzzy simulations

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A Multi-objective fuzzy programming Model for Coordinate Operations of a Supply Chain with Uncertain Demands

A Multi-objective Fuzzy Programming Model for Coordinate Ope...

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2012 IEEE 19th International Conference on Industrial Engineering and Engineering Management(IE&EM 2012)

作者： Jia-wang Xu Yi Zhang Li-qiang Zhao College of Economics and Management Shenyang Aerospace University Shenyang Institute of Automation Chinese Academy of Sciences

The coordinate operating process of a supply chain is considered. The supply chain is consisting of a manufacturer, a supplier and several customers, the semi- finished products of the supplier are raw materials of the manufacturer, demands of customers are uncertain, and the uncertainties of demands are described as fuzzy sets. A multi-objective fuzzy programming model for coordinate operations of the supply chain is constructed and a numerical example is proposed. The results of the numerical example shows that decision makers can obtain an optimal operations strategy by using the model proposed in this paper according to the level of uncertainties of demands, and the operation strategy possesses robustness in same ways.

关键词： Coordinate Operations fuzzy programming multi-objective programming supply chain uncertainty

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WEIGHTED ADDITIVE MODELS FOR SOLVING fuzzy GOAL programming PROBLEMS

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2008年第5期25卷 715-733页

作者： Yaghoobi, M. A. Jones, D. F. Tamiz, M. Univ Portsmouth Dept Math Management Math Grp Portsmouth PO1 3HF Hants England Shahid Bahonar Univ Kerman Fac Math & Comp Dept Stat Kerman Iran

Weighted additive models are well known for dealing with multiple criteria decision making problems. fuzzy goal programming is a branch of multiple criteria decision making which has been applied to solve real life problems. Several weighted additive models are introduced to handle fuzzy goal programming problems. These models are based on two approaches in fuzzy goal programming namely goal programming and fuzzy programming techniques. However, some of these models are not able to solve all kinds of fuzzy goal programming problems and some of them that appear in current literature suffer from a lack of precision in their formulations. This paper focuses on weighed additive models for fuzzy goal programming. It explains the oversights within some of them and proposes the necessary corrections. A new improved weighted additive model for solving fuzzy goal programming problems is introduced. The relationships between the new model and some of the existing models are discussed and proved. A numerical example is given to demonstrate the validity and strengths of the new model.

关键词： fuzzy goal programming goal programming fuzzy programming weighted additive models multiple criteria decision making

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Solving multi-level multi-objective linear programming problems through fuzzy goal programming approach

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APPLIED MATHEMATICAL MODELLING 2010年第9期34卷 2377-2387页

作者： Baky, Ibrahim A. Benha Univ Dept Basic Sci Benha Higher Inst Technol El Kalyoubia Egypt

In this paper, two new algorithms are presented to solve multi-level multi-objective linear programming (ML-MOLP) problems through the fuzzy goal programming (FGP) approach. The membership functions for the defined fuzzy goals of all objective functions at all levels are developed in the model formulation of the problem: so also are the membership functions for vectors of fuzzy goals of the decision variables, controlled by decision makers at the top levels. Then the fuzzy goal programming approach is used to achieve the highest degree of each of the membership goals by minimizing their deviational variables and thereby obtain the most satisfactory solution for all decision makers. The first suggested algorithm groups the membership functions for the defined fuzzy goals of the objective functions at all levels and the decision variables for each level except the lower level of the multi-level problem. The second proposed algorithm lexicographically solves MOLP problems of the ML-MOLP problem by taking into consideration the decisions of the MOLP problems for the upper levels. An illustrative numerical example is given to demonstrate the algorithms. (C) 2009 Elsevier Inc. All rights reserved.

关键词： Multi-objective linear programming Multi-level programming problems Goal programming fuzzy programming fuzzy goal programming

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Generalized fuzzy linear programming for decision making under uncertainty: Feasibility of fuzzy solutions and solving approach

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INFORMATION SCIENCES 2013年 241卷 12-27页

作者： Fan, Y. R. Huang, G. H. Yang, A. L. Univ Regina Fac Engn Regina SK S4S 0A2 Canada North China Elect Power Univ SC Resources & Environm Res Acad MOE Key Lab Reg Energy Syst Optimizat Beijing 102206 Peoples R China

In this study, a generalized fuzzy linear programming (GFLP) method is developed for dealing with uncertainties expressed as fuzzy sets. The feasibility of fuzzy solutions of the GFLP problem is investigated. A stepwise interactive algorithm (SIA) based on the idea of design of experiment is then advanced to solve the GFLP problem. This SIA method was implemented through (i) discretizing membership grade of fuzzy parameters into a finite number of alpha-cut levels, (ii) converting the GFLP model into an interval linear programming (ILP) submodel under every alpha-cut level, (iii) solving the ILP submodels through an interactive algorithm and obtaining the associated interval solutions, (iv) acquiring the membership functions of fuzzy solutions through statistical regression methods. A simple numerical example is then proposed to illustrate the solution process of the GFLP model through SIA. A comparison between the solutions obtained though SIA and Monte Carlo method is finally conducted to demonstrate the robustness of the SIA method. The results indicate that the membership functions for decision variables and objective function are reasonable and robust. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Decision making fuzzy programming fuzzy sets Optimization Monte Carlo Uncertainty

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A note on article "A tolerance approach to the fuzzy goal programming problems with unbalanced triangular membership function"

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第1期176卷 636-640页

作者： Yaghoobi, M. A. Tamiz, M. Univ Portsmouth Dept Math Portsmouth PO1 3HE Hants England Univ Kerman Fac Math & Comp Sci Kerman Iran

Kim and Whang use a tolerance approach for solving fuzzy goal programming problems with unbalanced membership functions [J.S. Kim, K. Whang, A tolerance approach to the fuzzy goal programming problems with unbalanced triangular membership function, European Journal of Operational Research 107 (1998) 614-624]. In this note it is shown that some results in that article are incorrect. The necessary corrections are proposed. (c) 2005 Elsevier B.V. All rights reserved.

关键词： fuzzy goal programming goal programming fuzzy programming

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fuzzy GOAL programming FOR MULTIOBJECTIVE TRANSPORTATION PROBLEMS

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JOURNAL OF APPLIED MATHEMATICS AND COMPUTING 2007年第1-2期24卷 449-460页

作者： Zangiabadi, M. Maleki, H. R. Kerman Unicv Dept Math & Comp Sci Kerman Iran Shiraz Univ Dept Basic Sci Shiraz Iran

Several fuzzy approaches can be considered for solving multiobjective transportation problem. This paper presents a fuzzy goal programming approach to determine an optimal compromise solution for the multiobjective transportation problem. We assume that each objective function has a fuzzy goal. Also we assign a special type of nonlinear (hyperbolic) membership function to each objective function to describe each fuzzy goal. The approach focuses on minimizing the negative deviation variables from 1 to obtain a compromise solution of the multiobjective transportation problem. We show that the proposed method and the fuzzy programming method are equivalent. In addition, the proposed approach can be applied to solve other multiobjective mathematical programming problems. A numerical example is given to illustrate the efficiency of the proposed approach.

关键词： Multiobjective decision making goal programming transportation problem membership function fuzzy programming

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A hybrid fuzzy-stochastic programming method for water trading within an agricultural system

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AGRICULTURAL SYSTEMS 2014年 123卷 71-83页

作者： Li, Y. P. Liu, J. Huang, G. H. North China Elect Power Univ Sino Canada Resources & Environm Res Acad MOE Key Lab Reg Energy Syst Optimizat Beijing 102206 Peoples R China

In this study, a hybrid fuzzy-stochastic programming method is developed for planning water trading under uncertainties of randomness and fuzziness. The method can deal with recourse water allocation problems generated by randomness in water availability and, at the same time, tackle uncertainties expressed as fuzzy sets in the trading system. The developed method is applied to a water trading program within an agricultural system in the Zhangweinan River Basin, China. Results can reflect the decisions for water allocation and crop irrigation under various flow levels;this allows corrective actions to be taken based on the predefined policies for cropping patterns and can thus help minimize the penalty due to water deficit. The results indicate that trading can release excess water while still keeping the same agricultural revenue obtained in a non-trading scheme. This implies that trading scheme is effective for obtaining high economic benefit, particularly for one water-resources scarcity region. Results also indicate that the effectiveness of the trading program is explicitly affected by uncertainties expressed as randomness and fuzziness, which challenges the users to make decisions of their water demands due to uncertain water availability. Sensitivity analysis is also conducted to analyze the impacts of trading costs, demonstrating that the trading efforts could become ineffective when the trading costs are too high. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： fuzzy programming Irrigation Optimization Stochastic analysis Water trading Uncertainty

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Solving fuzzy programming Problem with Recourse

Solving Fuzzy Programming Problem with Recourse

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The Sixth International Conference on Information and Management Sciences

作者： Shenghua Wang~1 Baohua Guo~2 ~(1,2)Department of Mathematics and Physics,North China Electric Power University,Baoding 071003,China

The fuzzy two-stage programming problem with discrete fuzzy vector is hard to *** this pa- per, in order to solve this class of model,we design a algorithm by which we solve its deterministic equivalent programming to... 详细信息

关键词： fuzzy programming fuzzy variable twostage expected value.

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Model Design for Transmission Congestion Management Based on fuzzy programming

Model Design for Transmission Congestion Management Based on...

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2009 Second International Workshop on Knowledge Discovery and Data Mining

作者： Yu Zhao College of Economics & Management, Huazhong Agricultural University, HZAU Wuhan,Hubei,P.R.China, Bo Zhao School of Mathematical Science&Computing Technology,Central South University, CSU Changsha,Hunan,P.R.China, Chunjie Qi College of Economics & Management, Huazhong Agricultural University, HZAU Wuhan,Hubei,P.R.China,

Based on data collected previously on the electricity market of the East China,we use stepwise regression method to find the approximate expression of the active power flow of each power sets on East China's certain electrical *** classified discussion is carried out according to the difference of the capacity in and out of merit in order to obtain a simple and reasonable rule for calculating the block *** on this,the objective programming model for output distribution of each unit is *** conditions step by step,and adjust the output allocation *** flexible factors defining membership function to change fuzzy programming into non-fuzzy programming,and use genetic algorithm to get *** model considers both safety and cost so that different network operators can get their preferred allocation plan.

关键词： electrical network transmission congestion management fuzzy programming multiobjective optimization model design

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