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Resource leveling in construction by genetic algorithm-based optimization and its decision support system application

delete2000-11-01
delete120
PRE
AI
S
Sou-Sen Leu *
C
Chung-Huei Yang
J
Jiun-Ching Huang
DOI：10.1016/S0926-5805(99)00011-4delete
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Abstract

Abstract

En 中文
Traditional analytical and heuristic approaches are inefficient and inflexible when solving construction resource leveling problems. A computational optimization technique, genetic algorithms (GAs), was employed in this study to overcome drawbacks of traditional construction resource leveling algorithms. The proposed algorithm can effectively provide the optimal or near-optimal combination of multiple construction resources, as well as starting and finishing dates of activities subjected to the objective of resource leveling. Furthermore, a prototype of a decision support system (DSS) for construction resource leveling was also developed. Construction planners can interact with the system to carry out ad hoc analysis through what-if queries. (C) 2000 Elsevier Science B.V. All rights reserved.
Keywords:
resource leveling
genetic algorithms
scheduling system
decision support
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Journal

Automation in Construction cover
Automation in Construction
IF:
11.5
Papers:
6.2K
Citations:
4.2W

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No organization information available