NDLI: A Multi-objective Genetic Algorithm Approach Based on the Uniform Design Metmod

Content Provider	IEEE Xplore Digital Library
Author	Xiaoshu Ma Jing Huo Qun Wang
Copyright Year	2010
Abstract	Many optimization problems in the scientific research and engineering practice can be modeled as multi-objective optimization problems. Effective algorithms for them is of not only important in scientific research, but also valuable in applications. In this paper, a new genetic algorithm for multi-objective optimization problems based on uniform design called BUMOGA is proposed combined with uniform design. The algorithm can find the sparse areas of non-dominated frontier, and explore the sparse area which can make the non-dominated solutions more uniform. The introductions of uniform crossover operator and single point crossover complex operator make up the defects of weak search capabilities of simulated binary crossover operator. The global convergence of the algorithm is proved, and effectiveness of the algorithm is demonstrated by the simulations. The computer simulations for five difficult standard benchmark functions also verify this fact.
Starting Page	160
Ending Page	164
File Size	731131
Page Count	5
File Format	PDF
ISBN	9781424491148
DOI	10.1109/CIS.2010.43
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis genetic algorithm multiobjective optimization Accuracy uniform design Computational modeling Evolutionary computation Educational institutions Optimization Convergence
Content Type	Text
Resource Type	Article

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