A novel collaborative iterative greedy algorithm for hybrid flowshop scheduling problem with batch processing machines and variable sublots-Reference-Cited by-同舟云学术

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A novel collaborative iterative greedy algorithm for hybrid flowshop scheduling problem with batch processing machines and variable sublots

Published:2023-09-07 Issue: Volume: Page:1-21
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Li Chengshuai¹,Han Yuyan¹,Zhang Biao¹,Wang Yuting¹,Li Junqing²,Gao Kaizhou³

Affiliation:

1. School of Computer Science, Liaocheng University, Liaocheng, People’s Republic of China

2. School of Computer Science, Shandong Normal University, Jinan, People’s Republic of China

3. Macau Institute of Systems Engineering, Macau University of Science and Technology, Macau, People’s Republic of China

Funder

Natural Science Foundation of Shandong Province

National Natural Science Foundation of China

Guangyue Young Scholar Innovation Team of Liaocheng University

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2023.2253925

Reference38 articles.

1. An effective iterated greedy algorithm for scheduling unrelated parallel batch machines with non-identical capacities and unequal ready times

2. Two-stage, single-lot, lot streaming problem for a $$1+2$$ 1 + 2 hybrid flow shop

3. A Hybrid Evolutionary Algorithm Using Two Solution Representations for Hybrid Flow-Shop Scheduling Problem

4. A survey of scheduling with parallel batch (p-batch) processing

5. Lot streaming in hybrid flowshop scheduling problem by considering equal and consistent sublots under machine capability and limited waiting time constraint

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1. Multi-agent deep reinforcement learning for dynamic reconfigurable shop scheduling considering batch processing and worker cooperation;Robotics and Computer-Integrated Manufacturing;2025-02

2. Combining meta-heuristics and Q-learning for scheduling lot-streaming hybrid flow shops with consistent sublots;Swarm and Evolutionary Computation;2024-12

3. Minimising makespan in distributed assembly hybrid flowshop scheduling problems;International Journal of Production Research;2024-08-02

4. An adaptive shuffled frog-leaping algorithm for parallel batch processing machines scheduling with machine eligibility in fabric dyeing process;International Journal of Production Research;2024-03-05

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