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Multiobjective Evolutionary Algorithms for solving Constrained Optimization Problems

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2 Author(s)
Sarker, R. ; Sch. of Inf. Technol. & Electr. Eng., Australian Defence Force Acad., Canberra, ACT ; Ray, T.

In this paper, we compare two multi-objective evolutionary algorithms by solving bi-objective linear and nonlinear constrained optimization problems. The problems considered are three instances of a realistic crop planning problem. The multiobjective algorithms compared are a well-known multi-objective evolutionary algorithm NSGAII and our own algorithm MCA. We discuss the solutions obtained and analyse the sensitivity of variables for multi-objective solutions. From our analysis, it can be concluded that there is still room for improvement in the performance of the evolutionary optimization algorithms for some of these optimization problems

Published in:

Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on  (Volume:2 )

Date of Conference:

28-30 Nov. 2005