Paper Info
Title
A bi-population based genetic algorithm for the resource-constrained project scheduling problem
Abstract
The resource-constrained project scheduling problem (RCP- SP) is one of the most challenging problems in project scheduling. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions for more challenging problem instances. In this paper, we present a new genetic algorithm (GA) that, in contrast of a conventional GA, makes use of two separate populations. This bi-population genetic algorithm (BPGA) operates on both a population of left-justified schedules and a population of right-justified schedules in order to fully exploit the features of the iterative forward/backward scheduling technique. Comparative computational results reveal that this procedure can be considered as today's best performing RCPSP heuristic.
Year
DOI
Venue
2005
10.1007/11424925_41
ICCSA (4)
Keywords
DocType
Volume
bi-population genetic algorithm,resource-constrained project scheduling problem,project scheduling,new genetic algorithm,conventional ga,rcpsp heuristic,challenging problem,separate population,challenging problem instance,heuristic procedure,genetic algorithm,population genetics,networks,graphs
Conference
3483
ISSN
ISBN
Citations 
0302-9743
3-540-25863-9
9
PageRank 
References 
Authors
0.61
9
2
Name
Order
Citations
PageRank
Dieter Debels12179.98
M Vanhoucke291955.85