A combined constraint-space, objective-space approach for determining high-dimensional maximal efficient faces of multiple objective linear programs

DOI10.1016/0377-2217(94)00199-5zbMath0913.90233OpenAlexW2171592970MaRDI QIDQ1266607

Richard J. Gallagher, Jerald P. Dauer

Publication date: 31 May 1999

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(94)00199-5

zbMATH Keywords

linear \(k\)-objective minimizationcharacterizations for efficient faces

Mathematics Subject Classification ID

Special polytopes (linear programming, centrally symmetric, etc.) (52B12) Multi-objective and goal programming (90C29) Linear programming (90C05)

Related Items (11)

A geometrical analysis of the efficient outcome set in multiple objective convex programs with linear criterion functions ⋮ Unnamed Item ⋮ Adjacency based method for generating maximal efficient faces in multiobjective linear programming ⋮ Constructing efficient solutions structure of multiobjective linear programming ⋮ Hybrid approach for solving multiple-objective linear programs in outcome space ⋮ On the computation of all supported efficient solutions in multi-objective integer network flow problems ⋮ An algorithm based on facial decomposition for finding the efficient set in multiple objective linear programming ⋮ Outcome space partition of the weight set in multiobjective linear programming ⋮ Branch-and-bound variant of an outcome-based algorithm for optimizing over the efficient set of a bicriteria linear programming problem ⋮ New closedness results for efficient sets in multiple objective mathematical programming ⋮ The maximal descriptor index set for a face of a convex polyhedral set and some applications

Uses Software

• ADBASE
• EFFACET

Cites Work

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• Finding all maximal efficient faces in multiobjective linear programming
• Determination of the efficient set in multiobjective linear programming
• Constructing the set of efficient objective values in linear multiple objective transportation problems
• Saddle points of Hamiltonian systems in convex problems of Lagrange
• The Enumeration of the Set of All Efficient Solutions for a Linear Multiple Objective Program

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