Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26134
Title: Genetic algorithm optimized resource activity critical path method
Authors: Wang, P
Lu, M
Issue Date: 2002
Publisher: IEEE
Source: 2002 International Conference on Machine Learning and Cybernetics, 2002 : proceedings : 4-5 November 2002, v. 4, p. 1978-1982 How to cite?
Abstract: This paper presents enhanced version of resource-activity critical path method (RACPM) optimized by genetic algorithms (GA-RACPM) for resource-constrained project scheduling. The GA formulation is given and the GA-RACPM has been coded into a computer program, which is then used to solve a benchmark problem in the literature. The results show that GA-RACPM has greatly improved the computing performance and set a new benchmark for the total project time. General guidelines on applying GA-RACPM in practical project scheduling are also given based on the results of testing GA-RACPM in a series of projects.
URI: http://hdl.handle.net/10397/26134
ISBN: 0-7803-7508-4
DOI: 10.1109/ICMLC.2002.1175383
Appears in Collections:Conference Paper

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