Loading...
A Bi-Population Based Genetic Algorithm for the Resource-Constrained Project Scheduling Problem
Debels, Dieter Vanhoucke, Mario
Debels, Dieter
Vanhoucke, Mario
Citations
Altmetric:
Publication Type
Working paper
Editor
Supervisor
Publication Year
2005
Journal
Book
Publication Volume
Publication Issue
8
Publication Begin page
Publication End page
Publication Number of pages
22
Collections
Abstract
The resource-constrained project scheduling problem (RCPSP) 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 local search scheduling technique. Comparative computational results reveal that this procedure can be considered as today's best performing RCPSP heuristic.
Research Projects
Organizational Units
Journal Issue
Keywords
Programme & Portfolio Management