Solving Multi-Objective Optimization Problems by a Bi-Objective Evolutionary Algorithm
Yuping Wang
Abstract
Yuping Wang
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.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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.
Key concepts: Benchmark (surveying), Evolutionary algorithm, Crossover, Mathematical optimization, Multi-objective optimization, Optimization problem, Computer science, Selection (genetic algorithm)