TY - GEN
T1 - A Robust Genetic Algorithm to Solve Multi-Skill Resource Constrained Project Scheduling Problem with Transfer Time and Uncertainty Skills
AU - Cai, Junqi
AU - Peng, Zhihong
AU - Ding, Shuxin
AU - Sun, Jingbo
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/9
Y1 - 2020/10/9
N2 - Multi-skill resource-constrained project scheduling problem (MS-RCPSP) is one of the most investigated problems in operations research. Most researches ignore transfer time of resources between activities, which is regularly en-countered in manufacturing and service industries. Traditional methods assume that the skill value of resource is fixed, but in practice, it changes with the influence of the environment. When using traditional approach, the optimizing procedure of the baseline project plan fails and leads to delays. To address this issue, we propose a robust model which employs a novel robust counterpart that is different from the previous literature. A new genetic algorithm using two new population initialization heuristic methods is proposed to find a robust schedule. Experiment shows the effectiveness of our proposed method in providing more robust schedules under resource skill uncertainty.
AB - Multi-skill resource-constrained project scheduling problem (MS-RCPSP) is one of the most investigated problems in operations research. Most researches ignore transfer time of resources between activities, which is regularly en-countered in manufacturing and service industries. Traditional methods assume that the skill value of resource is fixed, but in practice, it changes with the influence of the environment. When using traditional approach, the optimizing procedure of the baseline project plan fails and leads to delays. To address this issue, we propose a robust model which employs a novel robust counterpart that is different from the previous literature. A new genetic algorithm using two new population initialization heuristic methods is proposed to find a robust schedule. Experiment shows the effectiveness of our proposed method in providing more robust schedules under resource skill uncertainty.
UR - http://www.scopus.com/inward/record.url?scp=85098064495&partnerID=8YFLogxK
U2 - 10.1109/ICCA51439.2020.9264319
DO - 10.1109/ICCA51439.2020.9264319
M3 - Conference contribution
AN - SCOPUS:85098064495
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 1584
EP - 1589
BT - 2020 IEEE 16th International Conference on Control and Automation, ICCA 2020
PB - IEEE Computer Society
T2 - 16th IEEE International Conference on Control and Automation, ICCA 2020
Y2 - 9 October 2020 through 11 October 2020
ER -