Spreading Points Using Gradient and Tabu

Xiangyang Huang () and LiGuo Huang
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Xiangyang Huang: Capital Normal University
LiGuo Huang: Southern Methodist University

SN Operations Research Forum, 2023, vol. 4, issue 2, 1-11

Abstract: Abstract Large spreading (packing) problems are hard to be solved exactly. Consequently, heuristic approaches are usually used to find approximate solutions. In this paper, a hybrid heuristic method, consisting of a Neighborhood Tabu (NT) and a Perturbed Gradient (PG), is proposed for solving spreading points problems. NT applies an adaptive random technique to selecting promising candidate solutions from the neighborhood of the current local minimum and PG uses a neighborhood-based perturbed gradient algorithm to seek a better minimum, starting from the candidates. Two procedures work alternatively and cooperatively. When applied to some previously studied packings, the proposed method can improve the accuracy of the previous record solutions.

Keywords: Spreading; Packing; Minimum enclosing ball; Gradient; Tabu search (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s43069-023-00214-7

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