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- W2550097949 abstract "The resource-constrained project scheduling problem (RCPSP) is one of the most challenging problems in con- struction scheduling applications, in which optimal solutions are of great value to project planners. This paper presents a new adaptive hybrid genetic algorithm search simulator (AHGASS) for finding an optimal solution to the problem, and provides the strategies and practical procedures to develop the algorithm. Elitist genetic algorithm (EGA) developed is used for the global search, while random walk algorithm for the local search is incorporated into the EGA to overcome the drawbacks of general genetic algorithms, which are computationally intensive and premature convergence to a local solution. Computational experiments are presented to demonstrate the performance and accuracy of AHGASS. The pro- posed algorithm provides a comparable and competitive performance compared with the existing genetic algorithm (GA) hybrid heuristic methods. The findings demonstrate that AHGASS has significant promise for solving a large-sized RCPSP. Resume ´ : Le probleme d'ordonnancement de projet avec contrainte de ressources (RCPSP) est l'un des problemes posant les plus grands defis aux applications de determination des echeanciers de construction dans lesquelles les solutions opti- males sont d'une grande valeur pour les planificateurs en construction. Cet article presente un nouveau simulateur de re- cherche par algorithme genetique hybride et adaptatif (AHGASS) afin de decouvrir une solution optimale au probleme et fournit des strategies et des procedures pratiques pour developper cet algorithme. L'algorithme genetique elitiste (EGA) developpeest utilisepour la recherche globale alors que l'algorithme de marche aleatoire pour la recherche locale est in- corporedans l'EGA afin de surmonter les lacunes des algorithmes genetiques generaux, qui demandent beaucoup de temps d'ordinateur et qui convergent prematurement vers une solution locale. Des experiences de calcul sont presentees afin de demontrer le rendement et la precision de l'AHGASS. L'algorithme proposefournit un rendement comparable et competi- tif par rapport aux methodes heuristiques hybrides d'algorithmes generaux existantes. Les conclusions montrent que l'AHGASS est prometteur pour resoudre un RCPSP de grande dimension. Mots-cles: ressources, etablissement de calendrier, gestion de projet, optimisation, calcul de l'evolution, methodes hy- brids. (Traduit par la Redaction)" @default.
- W2550097949 created "2016-11-30" @default.
- W2550097949 creator A5055673439 @default.
- W2550097949 creator A5086213577 @default.
- W2550097949 date "2009-01-01" @default.
- W2550097949 modified "2023-09-23" @default.
- W2550097949 title "REVIEW / SYNTHESE Robust global and local search approach to resource-constrained project scheduling" @default.
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