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Title: Self-adaptive fitness formulation for constrained optimization
Authors: Farmani, Raziyeh
Wright, Jonathan A.
Keywords: Self-adaptive
Dynamic
Fitness
Genetic algorithms
Penalty
Issue Date: 2003
Publisher: © IEEE
Citation: FARMANI, R. and WRIGHT, J., 2003. Self-adaptive fitness formulation for constrained optimization. IEEE Transactions on Evolutionary Computation, 7 (5), pp. 445- 455
Abstract: A self-adaptive fitness formulation is presented for solving constrained optimization problems. In this method, the dimensionality of the problem is reduced by representing the constraint violations by a single infeasibility measure. The infeasibility measure is used to form a two-stage penalty that is applied to the infeasible solutions. The performance of the method has been examined by its application to a set of eleven test cases from the specialized literature. The results have been compared with previously published results from the literature. It is shown that the method is able to find the optimum solutions. The proposed method requires no parameter tuning and can be used as a fitness evaluator with any evolutionary algorithm. The approach is also robust in its handling of both linear and nonlinear equality and inequality constraint functions. Furthermore, the method does not require an initial feasible solution.
Description: This is a journal article. It was published in the journal IEEE Transactions on Evolutionary Computation [© IEEE) and is also available at: http://ieeexplore.ieee.org. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
URI: https://dspace.lboro.ac.uk/2134/3715
ISSN: 1089-778X
Appears in Collections:Published Articles (Civil and Building Engineering)

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