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A novel multi-objective optimization algorithm based on Lightning Attachment Procedure Optimization algorithm

delete2019-02-01
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A
Amin Foroughi Nematollahi
B
Behrooz Vahidi *
DOI:10.1016/j.asoc.2018.11.032delete
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Abstract

Abstract

En 中文
In this paper, a novel multi-objective optimization method based on a recently introduced algorithm known as Lightning Attachment Procedure Optimization (LAPO) is presented. The proposed algorithm is based on non-dominated sorting approach where the best solutions chosen from the Pareto Optimal Front (POF), based on crowding distance, are stored in a repository matrix called an Archive matrix. The procedure is performed such that the final best solutions are distributed evenly along the optimal PF. Then, the proposed algorithm is tested by some multi-objective optimization functions and some classical engineering problems also. The results are compared to those of four well-known methods and then discussed. The results are compared using 4 criteria which show how to select a POF close to the true POF, how the results are distributed, and how close the final results approximate all the possible outcomes of true POF. It is shown that the proposed method outperforms the other methods with regards to 3 criteria and yields comparable results regarding the last criteria. Superiority of the proposed method in finding the true POF while covering a wide range of possible optimal results is discussed in the results section. Therefore, it is concluded that the proposed method does an excellent job at solving a wide range of multi-objective optimization problems. (C) 2018 Elsevier B.V. All rights reserved.
Keywords:
Multi objective optimization method
Lightning Attachment Procedure Optimization
Non-dominated sorting
Evolutionary multi-objective optimization
Benchmark problem
Pareto optimal solutions
Meta-heuristic
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Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

A
Amirkabir University of Technology
Scholars:
1.1W
Papers: 1.1W
Citations: 1.0W
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