Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Variable Neighborhood Search for the Resource Constrained Project Scheduling Problem. / Goncharov, Evgenii N.
Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Revised Selected Papers. ed. / Igor Bykadorov; Vitaly Strusevich; Tatiana Tchemisova. Springer Gabler, 2019. p. 39-50 (Communications in Computer and Information Science; Vol. 1090 CCIS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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TY - GEN
T1 - Variable Neighborhood Search for the Resource Constrained Project Scheduling Problem
AU - Goncharov, Evgenii N.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - We consider the resource-constrained project scheduling problem (RCPSP) with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. Activities preemptions are not allowed. The problem with renewable resources is NP-hard in the strong sense. We propose a variable neighborhood search algorithm with two neighborhoods. Numerical experiments based on standard RCPSP test dataset j120 from the PCPLIB library demonstrated that the proposed algorithm produces better results than existing algorithms in the literature for large-sized instances. For some instances from the dataset j120 the best known heuristic solutions were improved.
AB - We consider the resource-constrained project scheduling problem (RCPSP) with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. Activities preemptions are not allowed. The problem with renewable resources is NP-hard in the strong sense. We propose a variable neighborhood search algorithm with two neighborhoods. Numerical experiments based on standard RCPSP test dataset j120 from the PCPLIB library demonstrated that the proposed algorithm produces better results than existing algorithms in the literature for large-sized instances. For some instances from the dataset j120 the best known heuristic solutions were improved.
KW - Project management
KW - Renewable resources
KW - Resource-constrained project scheduling problem
KW - Variable neighborhood search
UR - http://www.scopus.com/inward/record.url?scp=85076184267&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-33394-2_4
DO - 10.1007/978-3-030-33394-2_4
M3 - Conference contribution
AN - SCOPUS:85076184267
SN - 9783030333935
T3 - Communications in Computer and Information Science
SP - 39
EP - 50
BT - Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Revised Selected Papers
A2 - Bykadorov, Igor
A2 - Strusevich, Vitaly
A2 - Tchemisova, Tatiana
PB - Springer Gabler
T2 - 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019
Y2 - 8 July 2019 through 12 July 2019
ER -
ID: 22996018