Title

Application Of Genetic Algorithms In Resource Constrained Network Optimization

Abstract

There are limited solution techniques available for resource constrained project scheduling problems with stochastic task durations. Due to computational complexity, scheduling heuristics have been found useful for large deterministic problems. In this paper, we demonstrate the use of a genetic algorithm to optimize over a linear combination of scheduling heuristics. A simulation model is used to evaluate the performance of each combination of the heuristics selected by the genetic algorithm, and this performance information is used by the genetic algorithm to select the next combinations to evaluate. The genetic algorithm and simulation based approach is demonstrated using a multiple resource constrained project scheduling problem with stochastic task durations.

Publication Date

12-1-1995

Publication Title

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

Volume

4

Number of Pages

3059-3062

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

0029505623 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0029505623

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