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An improved genetic algorithm for the resource-constrained project scheduling problem Full article

Conference XIII International Conference Optimization and Applications
26-30 Sep 2022 , Петровац
Source Advances in Optimization and Applications : 13th International Conference, OPTIMA 2022, Petrovac, Montenegro, September 26–30, 2022, Revised Selected Papers
Compilation, Springer Cham. 2023. 197 c. ISBN 978-3-031-22990-9.
Journal Communications in Computer and Information Science
ISSN: 1865-0929
Output data Year: 2023, Volume: 1739, Pages: 35-47 Pages count : 13 DOI: 10.1007/978-3-031-22990-9_3
Tags Project management, Resource-constrained project, scheduling problem, Renewable resources ,Genetic algorithms ,PCPLIB
Authors Goncharov Evgenii N. 1,2
Affiliations
1 Sobolev Institute of Mathematics
2 Novosibirsk State University

Funding (1)

1 Sobolev Institute of Mathematics FWNF-2022-0019

Abstract: This paper presents an improved genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The schedules are constructed using a heuristic that builds active schedules based on priorities that takes into account the degree of criticality for the resources. The degree of resource's criticality is derived from the solution of a relaxed problem with a constraint on accumulative resources. The computational results with instances from the PCPLIB library validate the effectiveness of the proposed algorithm. We have obtain some of the best average deviations of the solutions from the critical path value. The best known solutions have been improved for some instances from the PCPLIB.
Cite: Goncharov E.N.
An improved genetic algorithm for the resource-constrained project scheduling problem
In compilation Advances in Optimization and Applications : 13th International Conference, OPTIMA 2022, Petrovac, Montenegro, September 26–30, 2022, Revised Selected Papers. – Springer Cham., 2023. – C.35-47. – ISBN 978-3-031-22990-9. DOI: 10.1007/978-3-031-22990-9_3 Scopus OpenAlex
Dates:
Accepted: Aug 17, 2022
Published print: Jan 1, 2023
Published online: Jan 1, 2023
Identifiers:
Scopus: 2-s2.0-85148040365
OpenAlex: W4313343007
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