Guided Local Search - An illustrative example in function optimisation

Voudouris, C

dc.contributor.author	Voudouris, C	en
dc.date.accessioned	2014-03-01T01:47:13Z
dc.date.available	2014-03-01T01:47:13Z
dc.date.issued	1998	en
dc.identifier.issn	13583948	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25176
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0032115381&partnerID=40&md5=613b4880eed40f750f9fdbca69237fe0	en
dc.subject.other	Algorithms	en
dc.subject.other	Combinatorial mathematics	en
dc.subject.other	Computer simulation	en
dc.subject.other	Problem solving	en
dc.subject.other	Scheduling	en
dc.subject.other	Guide local search (GLS)	en
dc.subject.other	Optimization	en
dc.title	Guided Local Search - An illustrative example in function optimisation	en
heal.type	journalArticle	en
heal.publicationDate	1998	en
heal.abstract	The Guided Local Search method has been successfully applied to a number of hard combinatorial optimisation problems from the well-known TSP and QAP to real-world problems such as frequency assignment and workforce scheduling. In this paper, it is demonstrated that the potential applications of GLS are not limited to optimisation problems of discrete nature but also to difficult continuous optimisation problems. Continuous optimisation problems arise in many engineering disciplines (such as electrical and mechanical engineering) in the context of analysis, design or simulation tasks. The problem examined gives an illustrative example of the behaviour of GLS, providing insights on the mechanisms of the algorithm.	en
heal.journalName	BT Technology Journal	en
dc.identifier.volume	16	en
dc.identifier.issue	3	en
dc.identifier.spage	46	en
dc.identifier.epage	50	en