FGP Approach for Solving Fractional Multiobjective Decision Making Problems using GA with Tournament Selection and Arithmetic Crossover

被引:3
作者
Chakraborti, Debjani [1 ]
Biswas, Papun [2 ]
Pal, Bijay Baran [3 ]
机构
[1] Narula Inst Technol, Dept Math, Kolkata 700109, WB, India
[2] JIS Coll Engn, Dept Elect Engn, Kalyani 741235, W Bengal, India
[3] Univ Kalyani, Dept Math, Kalyani 741235, W Bengal, India
来源
FIRST INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE: MODELING TECHNIQUES AND APPLICATIONS (CIMTA) 2013 | 2013年 / 10卷
关键词
Fuzzy programming; Goal programming; Fuzzy goal programming; Genetic algorithm; Multiobjective decision making;
D O I
10.1016/j.protcy.2013.12.389
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article presents an effective genetic algorithm (GA) based fuzzy goal programming (FGP) for modelling and solving multiobjective decision making (MODM) problems with fractional criteria. In the proposed approach, GA, inspired by the natural selection and population genetics, is introduced first for searching of solutions at different stages and thereby solving the problem. In the proposed GA scheme, tournament selection scheme, arithmetic crossover and uniform mutation are adopted to search a satisfactory solution in complex decision making environment. To illustrate the potential use of the approach, a numerical example is solved and compared with the solutions obtained in previous study. (C) 2013 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:505 / 514
页数:10
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