JOURNAL ARTICLE

Solving Multi-Objective Optimization Problems by a Bi-Objective Evolutionary Algorithm

Abstract

In this paper a novel model for multiobjective optimization problem is proposed first, in which the multiobjective optimization problem is transformed into a bi-objective optimization problem. In this bi-objective problem one objective is responsible for optimizing the quality of the solutions, and the other is to improve the distribution of the obtained nondominated solution set. Then a new crossover operator and selection scheme are designed. Based on these, a specific-designed evolutionary algorithm is presented. The simulations on five widely used benchmark problems are made and the results indicate that the proposed algorithm is efficient and outperforms the compared algorithms.

Keywords:
Benchmark (surveying) Evolutionary algorithm Crossover Mathematical optimization Multi-objective optimization Optimization problem Computer science Selection (genetic algorithm) Set (abstract data type) Evolutionary computation Algorithm Operator (biology) Estimation of distribution algorithm Scheme (mathematics) Mathematics Artificial intelligence

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Topics

Advanced Multi-Objective Optimization Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Control Systems Optimization
Physical Sciences →  Engineering →  Control and Systems Engineering
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