A new approach to choosing initial points in local search
type: Item
instance of: scholarly article
title: A new approach to choosing initial points in local search
zbMATH Open document ID: 0665.68050
DOI: 10.1016/0020-0190(89)90111-7
author: Wing Shing Wong
author: Robert J. T. Morris
published in: Information Processing Letters
publication date: 1989-01-01T00:00:00Z
review text: Local search algorithms for global combinatorial optimization are usually initialized with multiple random solutions. We show that for an arbitrary problem, the use of a systematic initial point procedure based on an arbitrary partitioning of the state space typically outperforms the random initial point procedure. We further show that for one class of search operators it is possible to partition the search space into u- spheres. The use of u-spheres to initialize the search process is then investigated experimentally and shown to be capable of yielding a computational advantage at no added computational cost.
Mathematics Subject Classification ID: 68P10
Mathematics Subject Classification ID: 90C27
zbMATH DE Number: 4088944
zbMATH Keywords: partition by spheres
zbMATH Keywords: multistart methods
zbMATH Keywords: Local search
zbMATH Keywords: combinatorial optimization
MaRDI profile type: Publication
full work available at URL: 0020-0190(89)90111-7
OpenAlex ID: W2046636186
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description: scientific article; zbMATH DE number 4088944