Box-constrained multi-objective optimization: A gradient-like method without “a priori” scalarization

The aim of this paper is the development of an algorithm to find the critical points of a box-constrained multi-objective optimization problem. The proposed algorithm is an interior point method based on suitable directions that play the role of gradient-like directions for the vector objective func...

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Veröffentlicht in:	European journal of operational research Jg. 188; H. 3; S. 662 - 682
Hauptverfasser:	Miglierina, E., Molho, E., Recchioni, M.C.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.08.2008 Elsevier Elsevier Sequoia S.A
Schriftenreihe:	European Journal of Operational Research
Schlagworte:	Algorithms Applied sciences Approximation Descent directions Exact sciences and technology Gradient-like method Interior point method Mathematical programming Multiple objective programming Operational research and scientific management Operational research. Management science Optimization Optimization algorithms Problem solving Pseudogradient Studies Vector space Interior point method Descent directions Gradient-like method Pseudogradient Multiple objective programming Pareto optimum Limit point Multiobjective programming Scalarization Critical point Non linear programming Dynamical system Approximation algorithm Constrained optimization Karush Kuhn Tucker method Objective function Gradient method Vector field
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
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