Multi-criteria branch and bound: A vector maximization algorithm for Mixed 0-1 Multiple Objective Linear Programming

Mavrotas, G; Diakoulaki, D

dc.contributor.author	Mavrotas, G	en
dc.contributor.author	Diakoulaki, D	en
dc.date.accessioned	2014-03-01T01:22:48Z
dc.date.available	2014-03-01T01:22:48Z
dc.date.issued	2005	en
dc.identifier.issn	0096-3003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16656
dc.subject	Branch and bound	en
dc.subject	Mixed integer programming	en
dc.subject	Multiple objective programming	en
dc.subject.classification	Mathematics, Applied	en
dc.subject.other	Algorithms	en
dc.subject.other	Computational methods	en
dc.subject.other	Decision making	en
dc.subject.other	Integer programming	en
dc.subject.other	Problem solving	en
dc.subject.other	Vectors	en
dc.subject.other	Branch and bounds	en
dc.subject.other	Mixed integer programming	en
dc.subject.other	Multi objective programming	en
dc.subject.other	Vector maximization algorithms	en
dc.subject.other	Linear programming	en
dc.title	Multi-criteria branch and bound: A vector maximization algorithm for Mixed 0-1 Multiple Objective Linear Programming	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.amc.2005.01.038	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.amc.2005.01.038	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	The paper describes the Multi-Criteria Branch and Bound (MCBB) algorithm. a vector maximization algorithm capable of deriving all efficient extreme points, for small and medium-sized Mixed 0-1 Multiple Objective Linear Programming (Mixed 0-1 MOLP). Particular emphasis is given to computational aspects aiming principally at accelerating the solution procedure. For facilitating the decision maker's search toward the most preferred efficient solution, the notion of efficient combinations of the binary variables is further exploited. It is also shown that the MCBB algorithm can be used in single objective problems (Mixed Integer LP problems) in order to determine all alternative optima, as well as in Mixed Integer MOLP problems and Pure 0-1 MOLP problems that frequently arise in practice. A computational experiment is included in the paper in order to illustrate the performance of the algorithm. (c) 2005 Elsevier Inc. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE INC	en
heal.journalName	Applied Mathematics and Computation	en
dc.identifier.doi	10.1016/j.amc.2005.01.038	en
dc.identifier.isi	ISI:000234583800003	en
dc.identifier.volume	171	en
dc.identifier.issue	1	en
dc.identifier.spage	53	en
dc.identifier.epage	71	en