Displaying similar documents to “A Dimension-Reduction Algorithm for Multi-Stage Decision Problems with Returns in a Partially Ordered Set”

Multi-objective geometric programming problem with Karush−Kuhn−Tucker condition using ϵ-constraint method

A. K. Ojha, Rashmi Ranjan Ota (2014)

RAIRO - Operations Research - Recherche Opérationnelle

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Optimization is an important tool widely used in formulation of the mathematical model and design of various decision making problems related to the science and engineering. Generally, the real world problems are occurring in the form of multi-criteria and multi-choice with certain constraints. There is no such single optimal solution exist which could optimize all the objective functions simultaneously. In this paper, -constraint method along with Karush−Kuhn−Tucker (KKT) condition...

A dimension-reduction algorithm for multi-stage decision problems with returns in a partially ordered set

Teodros Getachew, Michael M. Kostreva (2002)

RAIRO - Operations Research - Recherche Opérationnelle

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In this paper a two-stage algorithm for finding non- dominated subsets of partially ordered sets is established. A connection is then made with dimension reduction in time-dependent dynamic programming via the notion of a bounding label, a function that bounds the state-transition cost functions. In this context, the computational burden is partitioned between a time-independent dynamic programming step carried out on the bounding label and a direct evaluation carried out on a subset...

Large neighborhood improvements for solving car sequencing problems

Bertrand Estellon, Frédéric Gardi, Karim Nouioua (2007)

RAIRO - Operations Research

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The -hard problem of car sequencing has received a lot of attention these last years. Whereas a direct approach based on integer programming or constraint programming is generally fruitless when the number of vehicles to sequence exceeds the hundred, several heuristics have shown their efficiency. In this paper, very large-scale neighborhood improvement techniques based on integer programming and linear assignment are presented for solving car sequencing problems. The effectiveness...

A Generalization of Dynamic Programming for Pareto Optimization in Dynamic Networks

Teodros Getachew, Michael Kostreva, Laura Lancaster (2010)

RAIRO - Operations Research

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The Algorithm in this paper is designed to find the shortest path in a network given time-dependent cost functions. It has the following features: it is recursive; it takes place bath in a backward dynamic programming phase and in a forward evaluation phase; it does not need a time-grid such as in Cook and Halsey and Kostreva and Wiecek's "Algorithm One”; it requires only boundedness (above and below) of the cost functions; it reduces to backward multi-objective dynamic programming...

Extended VIKOR as a new method for solving Multiple Objective Large-Scale Nonlinear Programming problems

Majeed Heydari, Mohammad Kazem Sayadi, Kamran Shahanaghi (2010)

RAIRO - Operations Research

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The VIKOR method was introduced as a Multi-Attribute Decision Making (MADM) method to solve discrete decision-making problems with incommensurable and conflicting criteria. This method focuses on ranking and selecting from a set of alternatives based on the particular measure of “closeness” to the “ideal” solution. The multi-criteria measure for compromise ranking is developed from the – metric used as an aggregating function in a compromise programming method. In this paper, the...