FUZZY OPTIMIZATION MODEL BASED ON SYNTHESIZING EFFECT AND INEQUITY DEGREE

摘要

In this paper, based on the structure of fuzzy information and the mechanism of fuzzy optimization, we propose the concept of quasi-linear fuzzy number; by distinguishing principal index and secondary indices, we give the comparison method based on synthesizing effect combining with the compound qualification strategy of fuzzy information; starting from the essence of constraints, we give a fuzzy optimization model based on synthesizing effect and inequity degree (BID&SE-FOM), and propose an instructive fuzzy genetic algorithm based on principal operation and quasi-linear fuzzy numbers (PO+QL-FGA); Finally, we analyze the performance of PO+QL-FGA by using Markov chain theory, and further explain the application of quasi-linear fuzzy numbers by a concrete example.