Adaptive population-based simulated annealing for resource constrained job scheduling with uncertainty-Reference-Cited by-同舟云学术

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Adaptive population-based simulated annealing for resource constrained job scheduling with uncertainty

Published:2024-02-02 Issue:17 Volume:62 Page:6227-6250
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Thiruvady Dhananjay¹^ORCID,Nguyen Su²,Sun Yuan³,Shiri Fatemeh⁴,Zaidi Nayyar¹,Li Xiaodong⁵

Affiliation:

1. School of Information Technology, Deakin University, Geelong, Australia

2. School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, Australia

3. La Trobe Business School, La Trobe University, Melbourne, Australia

4. Faculty of Information Technology, Monash University, Melbourne, Australia

5. School of Science, RMIT University, Melbourne, Australia

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2024.2311183

Reference43 articles.

1. Proactive Algorithms for Job Shop Scheduling with Probabilistic Durations

2. Production Scheduling and Rescheduling with Genetic Algorithms

3. A Biased Random Key Genetic Algorithm with Rollout Evaluations for the Resource Constraint Job Scheduling Problem

4. Scheduling under uncertainty: Survey and research directions

5. Resource constrained project scheduling with uncertain activity durations

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Genetic-based Constraint Programming for Resource Constrained Job Scheduling;Proceedings of the Genetic and Evolutionary Computation Conference;2024-07-14

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