Self-Adaptive Population-Based Iterated Greedy Algorithm for Distributed Permutation Flowshop Scheduling Problem with Part of Jobs Subject to a Common Deadline Constraint-Reference-Cited by-同舟云学术

Self-Adaptive Population-Based Iterated Greedy Algorithm for Distributed Permutation Flowshop Scheduling Problem with Part of Jobs Subject to a Common Deadline Constraint

Published:2024-08 Issue: Volume:248 Page:123278
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Li Qiu-Ying,Pan Quan-Ke^ORCID,Sang Hong-Yan,Jing Xue-Lei^ORCID,Framiñán Jose M.,Li Wei-Min

Funder

Program of Shanghai Academic Research Leader

Shanghai Key Laboratory of Power Station Automation Technology

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference63 articles.

1. Distributed permutation flowshop scheduling problem with total completion time objective;Ali;OPSEARCH,2021

2. Automatic generation of iterated greedy algorithms for the non-permutation flow shop scheduling problem with total completion time minimization;Brum;Computers & Industrial Engineering,2022

3. A population-based iterated greedy algorithm to minimize total flowtime for the distributed blocking flowshop scheduling problem;Chen;Engineering Applications of Artificial Intelligence,2021

4. Maximizing total early work in a distributed two-machine flow-shop;Dolgui;Naval Research Logistics (NRL),2022

5. A tabu memory based iterated greedy algorithm for the distributed heterogeneous permutation flowshop scheduling problem with the total tardiness criterion;Feng;Expert Systems with Applications,2024

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