A method for finding well-dispersed subsets of non-dominated vectors for multiple objective mixed integer linear programs

We present an algorithm for generating a subset of non-dominated vectors of multiple objective mixed integer linear programming. Starting from an initial non-dominated vector, the procedure finds at each iteration a new one that maximizes the infinity-norm distance from the set dominated by the prev...

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Veröffentlicht in:European journal of operational research Jg. 180; H. 3; S. 1011 - 1027
Hauptverfasser: Sylva, John, Crema, Alejandro
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.08.2007
Elsevier
Elsevier Sequoia S.A
Schriftenreihe:European Journal of Operational Research
Schlagworte:
Applied sciences
Exact sciences and technology
Integer programming
Linear programming
Mathematical programming
Multiple objective programming
Operational research and scientific management
Operational research. Management science
Parametric programming
Studies
Vector space
Integer programming
Multiple objective programming
Parametric programming
Linear programming
Mixed integer programming
Multiobjective programming
ISSN:0377-2217, 1872-6860
Online-Zugang:Volltext
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Zusammenfassung:We present an algorithm for generating a subset of non-dominated vectors of multiple objective mixed integer linear programming. Starting from an initial non-dominated vector, the procedure finds at each iteration a new one that maximizes the infinity-norm distance from the set dominated by the previously found solutions. When all variables are integer, it can generate the whole set of non-dominated vectors.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2006.02.049