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Experiments on neighborhood combination strategies for bi-objective unconstrained binary quadratic programming problem
Xue, Li-Yuan1; Zeng, Rong-Qiang2,3; An, Wei4; Wang, Qing-Xian4; Shang, Ming-Sheng5
2017
摘要Local search is known to be a highly effective metaheuristic framework for solving a number of classical combinatorial optimization problems, which strongly depends on the characteristics of neighborhood structure. In this paper, we integrate the neighborhood combination strategies into the hypervolume-based multi-objective local search algorithm, in order to deal with the bi-objective unconstrained binary quadratic programming problem. The experimental results show that certain combinations are superior to others. The performance analysis sheds lights on the ways to further improvements. © 2017, Springer Nature Singapore Pte Ltd.
语种英语
DOI10.1007/978-981-10-6442-5_42
会议(录)名称8th International Symposium on Parallel Architectures, Algorithms, and Programming, PAAP 2017
页码444-453
通讯作者Zeng, Rong-Qiang (zrq@swjtu.edu.cn)
收录类别EI
会议地点Haikou, China
会议日期June 17, 2017 - June 18, 2017