Displaying similar documents to “Multi-objective geometric programming problem with Karush−Kuhn−Tucker condition using ϵ-constraint method”

Large neighborhood improvements for solving car sequencing problems

Bertrand Estellon, Frédéric Gardi, Karim Nouioua (2007)

RAIRO - Operations Research

Similarity:

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...

: Tools and techniques for an adaptive overlapping in SPMD programming

Pascal Havé (2010)

ESAIM: Mathematical Modelling and Numerical Analysis

Similarity:

During the development of a parallel solver for Maxwell equations by integral formulations and Fast Multipole Method (FMM), we needed to optimize a critical part including a lot of communications and computations. Generally, many parallel programs need to communicate, but choosing explicitly the way and the instant may decrease the efficiency of the overall program. So, the overlapping of computations and communications may be a way to reduce this drawback. We will see a implementation...

A Dimension-Reduction Algorithm for Multi-Stage Decision Problems with Returns in a Partially Ordered Set

Teodros Getachew, Michael M. Kostreva (2010)

RAIRO - Operations Research

Similarity:

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 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...

Minmax regret combinatorial optimization problems: an Algorithmic Perspective

Alfredo Candia-Véjar, Eduardo Álvarez-Miranda, Nelson Maculan (2011)

RAIRO - Operations Research

Similarity:

Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have been developed over the last 40 years. In our paper we essentially discuss a particular uncertainty model associated with combinatorial optimization problems, developed in the 90's and broadly studied in the past years. This approach named (in particular our emphasis is on the robust deviation criteria) is different from the classical approach for handling uncertainty, , where uncertainty...