A two-level parallel decomposition-based artificial bee colony method for dynamic multi-objective optimization problems

doi:10.1016/j.asoc.2023.110741

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A two-level parallel decomposition-based artificial bee colony method for dynamic multi-objective optimization problems

2023-11-01

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Yuyang Bai

Changsheng Zhang *

DOI：10.1016/j.asoc.2023.110741

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Abstract

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Many real-world multiple-objective optimization problems have objectives that change over time. These multiple-objective optimization problems are called dynamic multiple-objective optimization problems (DMOPs) and have received an increased attention. To track the changing Pareto front in DMOPs, the Pareto front at a certain moment needs to be obtained as efficiently as possible, which is challenging for most of existing methods. To this end, we propose a two-level parallel decomposition-based artificial bee colony method for solving DMOPs. To sufficiently accelerate the process of obtaining the Pareto front, a two-level parallel structure is designed in our method. In the first-level parallel structure, the dynamic multi-objective optimization problem at a certain moment is decomposed into a set of single-objective optimization problems that could be solved in parallel. In the second-level parallel structure, a parallel artificial bee colony algorithm is applied to solve each decomposed single -objective optimization problem. Specially, the parallel bee colony algorithm in our method is improved to support the exchange of information among neighbor problems, which is widely accepted to be effective in improving the efficiency of obtaining optimal solutions. To support the implementation of our improved parallel artificial bee colony algorithm, a two-level shared memory structure is designed. Our proposed method is compared with 4 widely used methods on CEC' 2018 multi-objective optimization benchmarks and two constrained dynamic multi-objective optimization problems. The experimental results show that our method outperforms other compared methods in efficiency while maintaining good scalability and convergence.(c) 2023 Published by Elsevier B.V.

Keywords:

Dynamic multi-objective optimization

Artificial bee colony algorithm

Decomposition-based strategy

Parallel computing technique