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2003

Exploiting the Marginal Profits of Constraints with Evolutionary Multi-Objective Optimization Techniques

8 years 11 months ago
Exploiting the Marginal Profits of Constraints with Evolutionary Multi-Objective Optimization Techniques
Many real-world search and optimization problems naturally involve constraint handling. Recently, quite a few heuristic methods were proposed to solve the nonlinear constrained optimization problems. However, the constraint-handling approaches in these methods have some drawbacks. In this paper, we gave a Multiobjective optimization problem based (MOP-based) formula for constrained single-objective optimization problems. We proposed a way to solve them by using multi-objective evolutionary algorithms (MOEAs). By simulation experiments, we find this approach for constraint handling not only can find the constrained optimality, but also can provide the decision maker (DM) with a group of trade-off solutions with slightly constraint violation and meanwhile with substantial gain in the objective function. This can enable the DM to have more freedom to choose his preferred solution and therefore exploit more profits in the margin of constraint violations, where the constraint violations ar...
Zhenyu Yan, Wei Zhi, Lishan Kang
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where ICAI
Authors Zhenyu Yan, Wei Zhi, Lishan Kang
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