DocumentCode :
1407946
Title :
Multiobjective programming using uniform design and genetic algorithm
Author :
Leung, Yiu-Wing ; Wang, Yuping
Author_Institution :
Dept. of Comput. Sci., Hong Kong Baptist Univ., Kowloon Tong, China
Volume :
30
Issue :
3
fYear :
2000
fDate :
8/1/2000 12:00:00 AM
Firstpage :
293
Lastpage :
304
Abstract :
The notion of Pareto-optimality is one of the major approaches to multiobjective programming. While it is desirable to find more Pareto-optimal solutions, it is also desirable to find the ones scattered uniformly over the Pareto frontier in order to provide a variety of compromise solutions to the decision maker. We design a genetic algorithm for this purpose. We compose multiple fitness functions to guide the search, where each fitness function is equal to a weighted sum of the normalized objective functions and we apply an experimental design method called uniform design to select the weights. As a result, the search directions guided by these fitness functions are scattered uniformly toward the Pareto frontier in the objective space. With multiple fitness functions, we design a selection scheme to maintain a good and diverse population. In addition, we apply the uniform design to generate a good initial population and design a new crossover operator for searching the Pareto-optimal solutions. The numerical results demonstrate that the proposed algorithm can find the Pareto-optimal solutions scattered uniformly over the Pareto frontier.
Keywords :
design of experiments; genetic algorithms; optimisation; search problems; Pareto frontier; Pareto optimality; crossover operator; experimental design; genetic algorithm; multiobjective programming; multiple fitness functions; normalized objective functions; search; uniform design; Algorithm design and analysis; Computer science; Design for experiments; Design methodology; Evolution (biology); Genetic algorithms; Genetic mutations; Mathematics; Scattering;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publisher :
ieee
ISSN :
1094-6977
Type :
jour
DOI :
10.1109/5326.885111
Filename :
885111
Link To Document :
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