Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Comparing a coevolutionary genetic algorithm for multiobjective optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
Genetic algorithms with memory-and elitism-based immigrants in dynamic environments
Evolutionary Computation
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A review of multiobjective test problems and a scalable test problem toolkit
IEEE Transactions on Evolutionary Computation
Utilization of modified simulating annealing as a tool for parallel computing
ACS'11 Proceedings of the 11th WSEAS international conference on Applied computer science
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In real-world problems, there exist many problems which their multi-objective vectors are required to be within the area in which something acts or operates. Many traditional methods scalarize the objective vector into a single objective, and some researchers are interested in the set known as Pareto optimal solution. However, in this paper, a new approach is proposed to solve the multi-objectives problems in which some elements of objective y = (y1, y2,...,ym) are requested to be balanced within its objective boundary. The proposed algorithm called genetic algorithm for objective boundary (GasOB scheme). The experimental results derived from the proposed algorithm have compared with the result derived by a linear search technique through the search space. In most cases, the results indicate that GAsOB can find the solution more efficiently than the linear search technique with a good customization of a number of eras and immigration rate.