Evolving many-objective dispatching rule pairs for unrelated parallel machine scheduling with sequence-dependent setup times-Reference-Cited by-同舟云学术

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Evolving many-objective dispatching rule pairs for unrelated parallel machine scheduling with sequence-dependent setup times

Published:2024-02-19 Issue: Volume: Page:1-22
ISSN:0305-215X
Container-title:Engineering Optimization
language:en
Short-container-title:Engineering Optimization

Author:

Zeng Chuangfeng¹,Liu Jianjun¹,Peng Chengfeng²,Chen Qingxin¹

Affiliation:

1. Key Laboratory of Computer lntegrated Manufacturing System, Guangdong University of Technology, Guangzhou, People's Republic of China

2. School of Physics, Electronics and Electrical Engineering, Xiangnan University, Chenzhou, People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2024.2305246

Reference32 articles.

1. Sequencing Rules and Due-Date Assignments in a Job Shop

2. Many-objective Optimization Using Evolutionary Algorithms: A Survey

3. A mathematical model and heuristic algorithms for an unrelated parallel machine scheduling problem with sequence-dependent setup times, machine eligibility restrictions and a common server

4. Unrelated parallel machine scheduling with new criteria: Complexity and models

5. A genetic programming learning approach to generate dispatching rules for flexible shop scheduling problems

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1. A hybrid genetic programming algorithm for the distributed assembly scheduling problems with transportation and sequence-dependent setup times;Engineering Optimization;2024-04-23

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