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

Junqi Cai, Zhihong Peng, Shuxin Ding, Jingbo Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2020 IEEE 16th International Conference on Control and Automation, ICCA 2020
PublisherIEEE Computer Society
Pages1584-1589
Number of pages6
ISBN (Electronic)9781728190938
DOIs
Publication statusPublished - 9 Oct 2020
Event16th IEEE International Conference on Control and Automation, ICCA 2020 - Virtual, Sapporo, Hokkaido, Japan
Duration: 9 Oct 202011 Oct 2020

Publication series

NameIEEE International Conference on Control and Automation, ICCA
Volume2020-October
ISSN (Print)1948-3449
ISSN (Electronic)1948-3457

Conference

Conference16th IEEE International Conference on Control and Automation, ICCA 2020
Country/TerritoryJapan
CityVirtual, Sapporo, Hokkaido
Period9/10/2011/10/20

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