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20 October 2022 A greedy strategy based iterative local search algorithm for orienteering problems
Wei Liu, Rui Wang, Kang Yang, Xu Yang, Tao Zhang
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Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123502S (2022) https://doi.org/10.1117/12.2652866
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China
Abstract
The orienteering problem (OP) is one of the most classical optimization problems, and the objective is to find a tour of some of the given nodes to obtain as much value as possible, with a maximum tour length constraint. Since the OP is an NP-hard problem, how to deal with it efficiently and effectively is always challenging. This study proposes to solve it through a greedy strategy based iterative local search algorithm (ILS-G). In detail, the greedy strategy is used to generate a good initial solution for accelerating the search process, and the iterative local search algorithm is proposed to further optimize the initial solution. An insertion operator, a 2-OPT operator, and a deletion operator are introduced in the iterative local search algorithm for updating the solution. Experimental results on instances with different problem sizes demonstrate the effectiveness and the efficiency of the proposed ILS-G.
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Wei Liu, Rui Wang, Kang Yang, Xu Yang, and Tao Zhang "A greedy strategy based iterative local search algorithm for orienteering problems", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123502S (20 October 2022); https://doi.org/10.1117/12.2652866
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KEYWORDS
Evolutionary algorithms
Optimization (mathematics)
Genetic algorithms
Mathematical modeling
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