Displaying similar documents to “An effective generalization of the direct support method.”

An algorithm for solving multiple objective integer linear programming problem

Moncef Abbas, Djamal Chaabane (2002)

RAIRO - Operations Research - Recherche Opérationnelle

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In the present paper a complete procedure for solving Multiple Objective Integer Linear Programming Problems is presented. The algorithm can be regarded as a corrected form and an alternative to the method that was proposed by Gupta and Malhotra. A numerical illustration is given to show that this latter can miss some efficient solutions. Whereas, the algorithm stated bellow determines all efficient solutions without missing any one.

Enumerating the Set of Non-dominated Vectors in Multiple Objective Integer Linear Programming

John Sylva, Alejandro Crema (2008)

RAIRO - Operations Research

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An algorithm for enumerating all nondominated vectors of multiple objective integer linear programs is presented. The method tests different regions where candidates can be found using an auxiliary binary problem for tracking the regions already explored. An experimental comparision with our previous efforts shows the method has relatively good time performance.

An algorithm for multiparametric min max 0-1-integer programming problems relative to the objective function

José Luis Quintero, Alejandro Crema (2005)

RAIRO - Operations Research - Recherche Opérationnelle

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The multiparametric min max 0-1-Integer Programming (0-1-IP) problem relative to the objective function is a family of min max 0-1-IP problems which are related by having identical constraint matrix and right-hand-side vector. In this paper we present an algorithm to perform a complete multiparametric analysis relative to the objective function.

An algorithm for multiparametric 0-1-Integer Programming problems relative to a generalized min max objective function

José Luis Quintero, Alejandro Crema (2009)

RAIRO - Operations Research

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The multiparametric 0-1-Integer Programming (0-1-IP) problem relative to the objective function is a family of 0-1-IP problems which are related by having identical constraint matrix and right-hand-side vector. In this paper we present an algorithm to perform a complete multiparametric analysis relative to a generalized min max objective function such that the min sum and min max are particular cases.

Tractable algorithms for chance-constrained combinatorial problems

Olivier Klopfenstein (2009)

RAIRO - Operations Research

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This paper aims at proposing tractable algorithms to find effectively good solutions to large size chance-constrained combinatorial problems. A new robust model is introduced to deal with uncertainty in mixed-integer linear problems. It is shown to be strongly related to chance-constrained programming when considering pure 0–1 problems. Furthermore, its tractability is highlighted. Then, an optimization algorithm is designed to provide possibly good solutions to chance-constrained...