Displaying similar documents to “Total Time Minimizing Transportation Problem”

Variants of the time minimization assignment problem.

Rita Malhotra, H. L. Bhatia (1984)

Trabajos de Estadística e Investigación Operativa

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The present paper develops techniques to solve two variants of the time minimization assignment problem. In the first, there are n jobs to be assigned to m establishments (m < n) in such a way that the time taken to complete all the jobs is the minimum, it being assumed that all the jobs are commenced simultaneously. The second variant is an extension of the first one in the sense that an additional constraint on the minimum number of jobs to be taken up by each establishment...

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.

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...