A primal-infeasible interior point algorithm for linearly constrained convex programming
Yanjin Wang, Pusheng Fei (2009)
Control and Cybernetics
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Yanjin Wang, Pusheng Fei (2009)
Control and Cybernetics
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Moshe Sniedovich, Stefan Voß (2006)
Control and Cybernetics
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Shyam S. Chadha (1989)
Trabajos de Investigación Operativa
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In this paper a multiparametric linear fractional functionals program, with parameters appearing only in the objective function, is generated. The optimum solution of this parametric program is supposed to satisfy the constraints as equations only. It is also shown that the set of parameters forms a convex polyhedron.
Dorota Kuchta (2004)
Control and Cybernetics
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Ladislav Lukšan (1982)
Kybernetika
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Moncef Abbas, Djamal Chaabane (2010)
RAIRO - Operations Research
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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.
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.