Given a weighted graph with a capacity associated to each node (element), the capacitated dispersion problem (CDP) consists in selecting a subset of elements satisfying a capacity constraint, in such a way that the minimum distance among them is maximized. The purpose of this work is to tackle this N P -hard problem, developing a simple, effective, and parameter-free method based on the solution-based tabu search algorithm ( SBTS ). Specifically, we propose a greedy construction heuristic to obtain high-quality initial solutions, and the use of three specific hash functions to identify the tabu status of candidate solutions. Moreover, to enhance the search, we propose the combination of three neighborhoods, including a new one, in which we implemented a constrained swapping strategy. The combination of all these elements results in a very efficient strategy. Extensible computational experiments are performed to get insights into the influences of the algorithmic components of SBTS , and to show that our proposal outperforms the state-of-the-art results. Finally, our solution approach is applied to a realistic location problem.
Solution-based tabu search for the capacitated dispersion problem
Zhi Lu,A. Martínez-Gavara,Jin‐Kao Hao,Xiangjing Lai
Published 2023 in Expert systems with applications
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- Publication year
2023
- Venue
Expert systems with applications
- Publication date
2023-03-01
- Fields of study
Mathematics, Computer Science, Engineering
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