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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 3

Intensification-driven tabu search for generalized dispersion problem

He Jiedong
Lu Zhi
Business School, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2025.07.0252

Abstract

Given an undirected complete graph, the Generalized Dispersion Problem (GDP) is to select a subset of nodes from the graph such that the minimum distance between any two nodes in the subset is maximized while the lower capacity limit and upper cost limit are satisfied. GDP is an NP-hard problem with important applications in undesirable facility location, social network analysis, ecological environment protection, etc. Although existing studies have proposed solution methods for solving GDP, they are limited especially when applied to large-scale GDP. This work proposes the first Intensification-driven Tabu Search (IDTS) algorithm for tackling GDP. Specifically, IDTS employs a fast greedy algorithm to construct an initial feasible solution, a joint neighborhood exploration strategy that integrates Add, Drop, and Constrained Swap neighborhoods to explore the search space, and a fast incremental calculation strategy to quickly evaluate the objective function value. It is important that IDTS explores the search space using an intensification-driven mechanism to increase the probability of finding a high-quality solution. Extensive experiments on three sets of 120 GDP benchmark instances from the literature show that IDTS competes very favorably with state-of-the-art algorithms, especially for large-scale GDP. Finally, additional experiments are provided to verify the role of the key ingredients of the algorithm.

Foundation Support

国家自然科学基金资助青年项目(72101149)
上海市浦江人才计划项目(22PJC080)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.07.0252
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 3

Publish History

[2025-11-17] Accepted Paper

Cite This Article

贺杰栋, 陆芷. 考虑容量和成本的最大最小多样性选址问题的强化驱动型禁忌搜索算法 [J]. 计算机应用研究, 2026, 43 (3). (2025-11-18). https://doi.org/10.19734/j.issn.1001-3695.2025.07.0252. (He Jiedong, Lu Zhi. Intensification-driven tabu search for generalized dispersion problem [J]. Application Research of Computers, 2026, 43 (3). (2025-11-18). https://doi.org/10.19734/j.issn.1001-3695.2025.07.0252. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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