A Novel Evolutionary Algorithm for Energy Efficient Scheduling in Flexible Job Shops-Reference-Cited by-同舟云学术

A Novel Evolutionary Algorithm for Energy Efficient Scheduling in Flexible Job Shops

Published:2022 Issue: Volume: Page:1-1
ISSN:1089-778X
Container-title:IEEE Transactions on Evolutionary Computation
language:
Short-container-title:IEEE Trans. Evol. Computat.

Author:

Ding Junwen¹^ORCID,Dauzere-Peres Stephane²^ORCID,Shen Liji³,Lu Zhipeng¹

Affiliation:

1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

2. Mines Saint-Etienne, Univ Clermont Auvergne, CNRS, UMR 6158 LIMOS, Gardanne, France and Department of Accounting and Operations Management, BI Norwegian Business School, Oslo, Norway

3. WHU – Otto Beisheim School of Management, Vallendar, Germany

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/4235/4358751/09953959.pdf?arnumber=9953959

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2. A two-stage cross-neighborhood search algorithm bridging different solution representation spaces for solving the hybrid flow shop scheduling problem;Swarm and Evolutionary Computation;2024-02

3. Energy Estimation and Production Scheduling in Job Shop Using Machine Learning;IEEE Access;2024

4. A Two-Stage Cross Neighborhood Search Algorithm Bridging Different Solution Representation Spaces for Solving the Hybrid Flow Shop Scheduling Problem;2023

5. A Two-Stage Cross Neighborhood Search Algorithm Bridging Different Solution Representation Spaces for Solving the Hybrid Flow Shop Scheduling Problem;2023