GA for fuzzy multi-mode resource-constrained project scheduling
 

Hongqi Pan and Chung-Hsing Yeh

School of Business Systems, Monash University, Clayton, Victoria 3800, Australia
 

Abstract

This paper deals with multiple mode resource-constrained project scheduling problems under uncertainty that often occur in practice. A fuzzy genetic algorithm (FGA) is first developed to solve the problem in a straightforward and robust manner. To improve its performance, FGA is combined with a tabu mechanism (FGA-tabu). FGA-tabu avoids revisit of previous search areas, thus saving unnecessary search time for the optimal solution. Both FGA and FGA-tabu developed can be applied to practical project scheduling problems of large sizes. The experiments conducted show that FGA-tabu outperforms FGA in terms of obtaining a good approximate optimal solution for resource-constrained project scheduling problems with fuzzy project completion times.

Keywords: Fuzzy set theory, Fuzzy multi-mode project scheduling, Renewable resources, Resource-constraints, Fuzzy genetic algorithm, Meta-heuristics, Tabu mechanism