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Modelisation et resolution de problemes d'optimisation combinatoire issus d'applications spatiales

Abstract : In this work we are concerned with combinatorial optimization problems stemming from space missions planning. These huge problems have some common features concerning the type of data, constraints and criteria to be optimized. We focus on linear programming for modeling and solving these problems, associated to methods for search space simplification, using decomposition or some constraint propagation techniques. We more particularly address two problems. The first one concerns a mission which aims at a scientific investigation of Mars. It consists in planning both communication slots between Martian probes and a satellite, and experiments on probes. We use linear integer programming to model and solve to optimality the sub-problem of communication slots planning, and we develop a decision-aid oriented method using constraint propagation for experiments planning. The second problem occurs in the context of the French program of Earth observing with satellites. It consists in selecting and scheduling images taken by one satellite in order to maximize a quality criterion. We give a linear model and we propose a column generation approach, based on the Dantzig-Wolfe decomposition of the model, to calculate upper bounds for this problem and in order to solve it.
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Submitted on : Wednesday, May 11, 2005 - 10:43:23 AM
Last modification on : Thursday, June 10, 2021 - 3:04:40 AM
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  • HAL Id : tel-00009238, version 1


Catherine Mancel. Modelisation et resolution de problemes d'optimisation combinatoire issus d'applications spatiales. Automatique / Robotique. INSA de Toulouse, 2004. Français. ⟨tel-00009238⟩



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