Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
An Improved Genetic Algorithm for the Resource-Constrained Project Scheduling Problem. / Goncharov, Evgenii N.
Communications in Computer and Information Science. Том 1739 Springer Science and Business Media Deutschland GmbH, 2022. стр. 35-47.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - An Improved Genetic Algorithm for the Resource-Constrained Project Scheduling Problem
AU - Goncharov, Evgenii N.
N1 - The study was carried out within the framework of the state contract of the Sobolev Institute of Mathematics (project FWNF-2022-0019).
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - https://www.scopus.com/inward/record.url?eid=2-s2.0-85148040365&partnerID=40&md5=9e4d0764e3d678d27e2118c8dc3ec3d2
UR - https://www.mendeley.com/catalogue/dc740862-15e2-3572-b50c-61191c20a608/
U2 - 10.1007/978-3-031-22990-9_3
DO - 10.1007/978-3-031-22990-9_3
M3 - Conference contribution
SN - 978-3-031-22989-3
VL - 1739
SP - 35
EP - 47
BT - Communications in Computer and Information Science
PB - Springer Science and Business Media Deutschland GmbH
ER -
ID: 45615056