TY - GEN

T1 - Cylindrical constraint evolutionary algorithm for multiobjective optimization

AU - Erfani, Tohid

AU - Utyuzhnikov, Sergei V.

PY - 2011

Y1 - 2011

N2 - This paper introduces a new iterative evolutionary algorithm, which is able to provide an evenly distributed set of solutions in multiobjective context. The method is different from the other evolutionary algorithms in two perspectives. First, instead of density information incorporated to find a diverse set of solutions, a hypercylinder is introduced as a new constraint to the problem. Searching for the solution within this hypercylinder guarantees the evenly generated solutions at the end of the optimization process. Second, a fitness function is constructed to handle the problem constraints and meanwhile minimize the distance of the solution to the true optimum frontier. In addition, the method is developed in such a way that it can be easily implemented in searching the preferable region of the search space. The algorithm behaviour is tested on different test cases and the results are compared in both convergence and diversity to those of other well known approaches to demonstrate the efficacy of the proposed method.

AB - This paper introduces a new iterative evolutionary algorithm, which is able to provide an evenly distributed set of solutions in multiobjective context. The method is different from the other evolutionary algorithms in two perspectives. First, instead of density information incorporated to find a diverse set of solutions, a hypercylinder is introduced as a new constraint to the problem. Searching for the solution within this hypercylinder guarantees the evenly generated solutions at the end of the optimization process. Second, a fitness function is constructed to handle the problem constraints and meanwhile minimize the distance of the solution to the true optimum frontier. In addition, the method is developed in such a way that it can be easily implemented in searching the preferable region of the search space. The algorithm behaviour is tested on different test cases and the results are compared in both convergence and diversity to those of other well known approaches to demonstrate the efficacy of the proposed method.

KW - Cylindrical constraint method

KW - Evolutionary algorithms

KW - Evolutionary optimization

KW - Genetic algorithm

KW - Multiobjective optimization

UR - http://www.scopus.com/inward/record.url?scp=84862201815&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84862201815

SN - 9789898425836

T3 - ECTA 2011 FCTA 2011 - Proceedings of the International Conference on Evolutionary Computation Theory and Applications and International Conference on Fuzzy Computation Theory and Applications

SP - 184

EP - 189

BT - ECTA 2011 FCTA 2011 - Proceedings of the International Conference on Evolutionary Computation Theory and Applications and International Conference on Fuzzy Computation Theory and Applications

T2 - International Conference on Evolutionary Computation Theory and Applications, ECTA 2011 and International Conference on Fuzzy Computation Theory and Applications, FCTA 2011

Y2 - 24 October 2011 through 26 October 2011

ER -