An Efficient Simulation Algorithm for Resource-Constrained Project Scheduling Problem
L. Peng, P. Wuliang*
Identifiers and Pagination:Year: 2014
First Page: 9
Last Page: 13
Publisher Id: TOMEJ-8-9
Article History:Received Date: 11/11/2013
Revision Received Date: 11/02/2014
Acceptance Date: 03/03/2014
Electronic publication date: 21/3/2014
Collection year: 2014
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Since Resource-Constrained Project Scheduling Problem (RCPSP) is a well-known NP-hard problem, it is difficult to solve large-scale practical cases by using traditional exact algorithms. Genetic algorithm (GA) is a kind of intelligent algorithm for approximate optimization, which can ascertain global optimization or suboptimal solution within a reasonable time. This article presented a new simulation algorithm by using GA for solving Resource-Constrained Project Scheduling Problem. In the algorithm, the activity adjacency matrix and priority-based preemptive resource conflict resolution are used to prevent chromosome from generating infeasible schedules. Finally, the method was tested with an actual machine and electricity project case, and the results show that the presented method is efficient and practical for practical project cases.