By Topic

Fuzzy multiobjective 0-1 programming through revised genetic algorithms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
H. Yano ; Sch. of Humanities & Social Sci., Nagoya Univ., Japan ; M. Sakawa ; T. Shibano

We consider multi-objective 0-1 programming problems and propose the fuzzy decision making method based on revised genetic algorithms. In the proposed method, by considering the imprecise nature of human judgements, it is assumed that the decision maker (DM) has a fuzzy goal for each of the objective functions and adopt the minimum-operator for combining the membership functions for fuzzy goals of the DM. Then the formulated problem can be reduced to the usual 0-1 programming problems. We propose the revised genetic algorithm in which the “random 0-1 reverse method” is introduced to deal with the linear constraints whose parameters may be positive or negative. We apply the proposed method to two types of problems: the real-world decision making problem, i.e., the media selection planning problem; and the numerical examples which involves 3 objectives, 30 variables and 5, 10 or 15 constraints, and whose parameters are generated at random

Published in:

Knowledge-Based Intelligent Electronic Systems, 1998. Proceedings KES '98. 1998 Second International Conference on  (Volume:1 )

Date of Conference:

21-23 Apr 1998