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On a generalized fuzzy goal optimization for solving fuzzy multi-objective linear programming problems

JOURNAL OF INTELLIGENT & fuzzy SYSTEMS 2007年第1期18卷 83-97页

作者： Lu, Jie Wu, Fengjie Zhang, Guangquan Univ Technol Sydney Fac Informat Technol Sydney NSW 2007 Australia

Many organizational decision problems can be formulated by multi-objective linear programming (MOLP) models. Referring to the imprecision inherent in human judgments, uncertainty may be incorporated in the parameters of an MOLP model when it is established, which is called a fuzzy MOLP (FMOLP) problem. What is an optimal solution for an FMOLP problem is the first issue to deal with in this study. The second issue is how to effectively derive an optimal solution for an FMOLP problem since uncertainty is also reflected in a solution process of an FMOLP problem. By introducing three types of comparison of fuzzy numbers and an adjustable satisfactory degree alpha in this study, a new solution concept of FMOLP is given. For handling the second issue, this study develops an interactive fuzzy goal optimization method which provides an interactive fashion with decision makers during their solution process and allows decision makers to give their fuzzy goals in any forms of membership functions. An illustrative example gives the details of the solution concept and the proposed method.

关键词： optimization fuzzy programming multi-objective linear programming interactive decision-making method

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A Goal programming Procedure for Solving Interval Valued Multiobjective Fractional programming Problems

A Goal Programming Procedure for Solving Interval Valued Mul...

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16th International Conference on Advanced Computers and Communications

作者： Pal, Bijay Baran Sen, Shyamal Univ Kalyani Dept Math Kalyani 741235 W Bengal India BKC Coll Dept Math Kolkata 700108 W Bengal India

ISBN: (纸本)9781424429622

This article presents a goal programming (GP) procedure for solving interval valued multiobjective fractional programming problems (MOFPPs) with interval objective functions in an inexact environment. In the proposed approach, the interval objective functions are first converted into the standard objective goals in the fractional GP formulation by using the interval arithmetic technique. Then, in the decision process, the fractional goals are transformed into the linear goals by linearization approach [31] studied previously. In solution process, the executable GP model of the problem is formulated with the objective to minimize the regret with the view to achieve the goals in their specified ranges and thereby arriving at a most satisfactory solution in the decision making environment. Two numerical examples are solved to illustrate the proposed approach and the model solution of one problem is compared with the solution of a fuzzy programming approach [28] studied previously.

关键词： Fractional programming fuzzy programming fuzzy Goal programming Interval programming Interval Arithmetic

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Supply Chain Network Design Based on fuzzy Neural Network and PSO

Supply Chain Network Design Based on Fuzzy Neural Network an...

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IEEE International Conference on Automation and Logistics

作者： Huang, Yuansheng Qiu, Zilong Liu, Qingchao N China Elect Power Univ Dept Econ & Management Baoding Hebei Province Peoples R China

ISBN: (纸本)9781424425020

This paper designs supply chain network in uncertain environment, in which the demands of customers are assumed to be random variables, and the operation costs are considered as fuzzy numbers. After modeling by fuzzy programming, a fuzzy neural network optimized by particle swarm optimization is presented to solve the established model. Through an example, compared with the traditional fuzzy neural network, it is proved that the presented method has advantage in calculation efficiency.

关键词： Supply Chain Network Design Uncertainty fuzzy programming fuzzy Neural Network PSO

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A Linear Goal programming Procedure for Academic Personel Management Problems in University System

A Linear Goal Programming Procedure for Academic Personel Ma...

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IEEE Region 10 Colloquium/3rd International Conference on Industrial and Information Systems

作者： Pal, Bijay Baran Sen, Shyamal Univ Kalyani Dept Math Kalyani 741235 West Bengal India Brahmananda Keshab Chandra Coll Dept Math Kolkata 7000108 India

ISBN: (纸本)9781424428052

This article describes a goal programming (GP) procedure for proper allocation of teaching personnel to the teaching departments for smooth functioning of the academic activities of a university. In the academic resource planning context, both the crisp and fuzzy goal objectives which are frequently involved with the problem are discussed. Again, certain ratios in the fractional forms which are inherently associated to the problem are also taken into consideration. In the model formulation, achievement of the highest membership value (unity) of the membership functions of the defined fuzzy goal as well as attainment of the prescribed goal levels of the crisp goals to the extent possible are considered. In the solution process, the fractional goals are transformed into the linear goals by using the linear transformation approach [1] studied previously. A case study of University of Kalyani, West Bengal, India is considered to expound the potential use of the proposed model.

关键词： fuzzy goal programming fuzzy programming fractional programming goal programming membership goal

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Multiple Criteria Mathematical programming and data mining

Multiple Criteria Mathematical Programming and data mining

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8th International Conference on Computational Science

作者： Shi, Yong Liu, Rong Yan, Nian Chen, Zhenxing Chinese Acad Sci Res Ctr Fictitious Econ & Data Sci Beijing 100080 Peoples R China Univ Nebraska Coll Informat Sci & Technol Omaha NE 68182 USA Grad Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China

ISBN: (纸本)9783540693833

Recently, researchers have extensively applied quadratic programming into classification, known as V. Vapnik's Support Vector Machine, as well as various applications. However, using optimization techniques to deal with data separation and data analysis goes back to more than forty years ago. Since 1998, the authors and their colleagues extended such a research idea into classification via multiple criteria linear programming (MCLP) and multiple criteria quadratic programming (MQLP). The purpose of the paper is to share our research results and promote the research interests in the community of computational sciences. These methods are different from statistics, decision tree induction, and neural networks. In this paper, starting from the basics of Multiple Criteria Linear programming (MCLP), we further discuss penalized MCLP Multiple Criteria Quadratic programming (MCQP), Multiple Criteria fuzzy Linear programming, Multi-Group Multiple Criteria Mathematical programming, as well as regression method by Multiple Criteria Linear programming. A brief summary of applications of Multiple Criteria Mathematical programming is also provided.

关键词： multi-criteria programming MCLP MCQP data mining classification regression fuzzy programming

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Credibility-based Core Knowledge Selection with fuzzy Information

Credibility-based Core Knowledge Selection with Fuzzy Inform...

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IEEE International Conference on Service Operations and Logistics and Informatics

作者： Pang, Jinhui Zhang, Qiang Beijing Inst Technol Adm Inst Informat Resources Beijing 100081 Peoples R China Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China

ISBN: (纸本)9781424420124

Managing core knowledge can present considerable challenges for long-term sustainable competitive advantages. The crux among knowledge management is how to effectively select core knowledge from various knowledge-based assets while maintaining tight control over intellectual properties. Owing to linguistic or uncertain concepts frequently represented in decision data, evaluations of real situations should be assumed to be fuzzy numbers. The paper proposes an approach to core knowledge selection with fuzzy information. Using the conceptual framework developed by Lin and Liu (2007), we focus on criteria evaluation and comprehensive procedure that have been previously associated with group decision system. We explore the choice-function which is an aggregating consistency of decision group and provide a fuzzy programming model of seeking core knowledge. fuzzy constraints are also considered in the model. Credibility measure is applied to solve the proposed model so that it can embody well the group preference level. Results of an example further show that the approach which fits into the general framework can successfully identify core knowledge worthy of attention.

关键词： Knowledge management Core knowledge fuzzy programming Credibility measure

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A family of optimization based data mining methods

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10th Asia-Pacific Web Conference and Workshops

作者： Shi, Yong Liu, Rong Yan, Nian Chen, Zhenxing Chinese Acad Sci Res Ctr Fictitious Econ & Data Sci Beijing 100080 Peoples R China Grad Univ Acad Sciences Sch Math Sci Beijing 100049 Peoples R China Univ Nebraska Coll Informat Sci & Tech Omaha NE USA

ISBN: (纸本)9783540788485

An extensive review for the family of multi-criteria programming data mining models is provided in this paper. These models are introduced in a systematic way according to the evolution of the multi-criteria programming. Successful applications of these methods to real world problems are also included in detail. This survey paper can serve as an introduction and reference repertory of multi-criteria programming methods helping researchers in data mining.

关键词： multi-criteria programming data mining classification regression fuzzy programming credit scoring network intrusion detection

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Operation for a new kind of fuzzy genetic algorithm based on the transformation of the principle index

Operation for a new kind of fuzzy genetic algorithm based on...

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5th International Conference on Machine Learning and Cybernetics

作者： Li, Fa-Chao Jin, Chen-Xia Yue, Pan-Xiang Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang 050018 Peoples R China

By using the restricted and complementary relationship of the principle and secondary indexes, providing the description of the compound quanti. cation of the fuzzy number, and analyzing the essential characteristic of fuzzy decision, we propose a kind of fuzzy genetic algorithm based on the principle index (PO-FGA for short) to deal with the fuzzy optimization and programming problems with fuzzy coefficients, fuzzy variables and fuzzy constraints. The concrete solution method is presented in accordance with the strategy of the unconditional penality transformation with conditional constrains. Then consider its convergence by using Markov chain theory and analyze its performance through two examples. All these indicate that this kind of algorithm is of faster speed of convergence, smaller number of iterations, has lower chances of trapping into the state of premature convergence and can be widely used in many problems of optimization.

关键词： fuzzy number fuzzy programming principle index fuzzy genetic algorithms Markov chain

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A Linkage Of Markdown Pricing With Aggregate Production Planning

A Linkage Of Markdown Pricing With Aggregate Production Plan...

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IEEE International Conference on Service Operations and Logistics and Informatics

作者： Zhu, Wenyun Chung, William City Univ Hong Kong Dept Management Sci Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781424420124

This paper is to study the significance of the cooperation between the markdown policy and the aggregate planning so as to simulate the cooperation between retailers and manufacturers. A fuzzy nonlinear programming model, named Aggregate Production Planning-Markdown Pricing Model (APP-MP), is established by integrating the markdown model into Aggregate Production Planning model. Due to the uncertainty of business information and environment, some cost elements are considered to be fuzzy number so that the objective function is fuzzy in nature. The fuzzy programming model is transformed into a crisp parametric model to be solved. The parametric APP-MP is able to help the retailer and the manufacturer flexibly make the pricing decisions, including the magnitude and time of markdown, and production decisions based on different satisfaction levels so that greater profits could be obtained. The example solution shows that the cooperation definitely increases the profits.

关键词： aggregate production planning markdown pricing cooperation fuzzy programming

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Solving fuzzy two-stage programming problem with discrete fuzzy vector

Solving fuzzy two-stage programming problem with discrete fu...

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6th International Conference on Machine Learning and Cybernetics

作者： Wang, Sheng-Hua Guo, Bao-Hua Zhang, Qun-Feng North China Elect Power Univ Dept Math & Phys Baoding 071003 Peoples R China Hebei Univ Fac Math & Comp Sci Baoding 071002 Peoples R China

ISBN: (纸本)9781424409723

The fuzzy two-stage programming problem with discrete fuzzy vector is hard to solve. In this paper, in order to solve this class of model, we design a algorithm by which we solve its deterministic equivalent programming to obtain optimal solution. Finally, two numerical examples are provided for showing the effectiveness of this algorithm.

关键词： fuzzy programming fuzzy variable two-stage expected value

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