Lexicographic optimization‐based clustering search metaheuristic for the multiobjective flexible job shop scheduling problem-Reference-Cited by-同舟云学术

Lexicographic optimization‐based clustering search metaheuristic for the multiobjective flexible job shop scheduling problem

Published:2019-11 Issue:5 Volume:28 Page:2733-2758
ISSN:0969-6016
Container-title:International Transactions in Operational Research
language:en
Short-container-title:Intl. Trans. in Op. Res.

Author:

Bissoli Dayan C.¹,Zufferey Nicolas²,Amaral André R. S.³

Affiliation:

1. Computer Department (DCOMP) Federal University of Espírito Santo (UFES) Alegre, ES, 29500‐000 Brazil

2. Geneva School of Economics and Management (GSEM) University of Geneva 1211 Geneva Switzerland

3. Graduate School of Computer Science (PPGI) Federal University of Espírito Santo (UFES) Vitória ES 29075‐910 Brazil

Funder

Fundação de Amparo à Pesquisa e Inovação do Espírito Santo

Publisher

Wiley

Subject

Management of Technology and Innovation,Management Science and Operations Research,Strategy and Management,Computer Science Applications,Business and International Management

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/itor.12745

Reference52 articles.

1. Altoé W.A.S. Bissoli D.C. Mauri G.R. Amaral A.R.S. 2018. A clustering search metaheuristic for the bi‐objective flexible job shop scheduling problem. XLIV CLEI—Latin American Computing Conference São Paulo.

2. Lexicographic optimization based MPC: Simulation and experimental study

3. Bissoli D.C. Amaral A.R.S. 2018. A hybrid iterated local search metaheuristic for the flexible job shop scheduling problem. XLIV CLEI—Latin American Computing Conference São Paulo.

4. Routing and scheduling in a flexible job shop by tabu search

5. Brucker P. 2007. The job‐shop problem: old and new challenges. Proceedings of the MISTA Conference Paris pp. 15–22.

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