An improved multi-objective evolutionary algorithm based on decomposition for energy-efficient permutation flow shop scheduling problem with sequence-dependent setup time
Author:
Affiliation:
1. Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing 100084, People’s Republic of China
Funder
the Key R&D Project of China
the National Science Fund for Distinguished Young Scholars of China
Publisher
Informa UK Limited
Subject
Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management
Link
https://www.tandfonline.com/doi/pdf/10.1080/00207543.2018.1504251
Reference33 articles.
1. The third comprehensive survey on scheduling problems with setup times/costs
2. Energy-conscious unrelated parallel machine scheduling under time-of-use electricity tariffs
3. Handling multiple objectives with particle swarm optimization
4. Energy-efficient scheduling for a flexible flow shop using an improved genetic-simulated annealing algorithm
5. A fast and elitist multiobjective genetic algorithm: NSGA-II
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