A Robust Genetic Algorithm to Solve Multi-Skill Resource Constrained Project Scheduling Problem with Transfer Time and Uncertainty Skills

2020 IEEE 16TH INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION (ICCA)(2020)

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摘要
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.
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关键词
genetic algorithm,multiskill resource constrained project scheduling problem,transfer time,uncertainty skills,MS-RCPSP,population initialization heuristic methods,operations research
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