Application of genetic algorithms in resource constrained network optimization

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, the authors 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