A Two-Phase Hybrid Approach for the Hybrid Flexible Flowshop with Transportation Times

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Abstract

We present a two-phase heuristic approach for the Hybrid Flexible Flowshop with Transportation Times (HFFTT) which combines a metaheuristic with constraint programming (CP). In the first phase an adapted version of a state-of-the-art metaheuristic for the Hybrid Flowshop [15] generates an initial solution. In the second phase, a CP approach reoptimizes the solution with respect to the last stages. Although this research is still in progress, the initial computational results are very promising. In fact, we show that the proposed hybrid approach outperforms both the adapted version of [15] and earlier CP approaches.

Original languageEnglish
Title of host publicationIntegration of Constraint Programming, Artificial Intelligence, and Operations Research - 19th International Conference, CPAIOR 2022, Proceedings
EditorsPierre Schaus
PublisherSpringer Science and Business Media Deutschland GmbH
Pages1-13
Number of pages13
ISBN (Print)9783031080104
DOIs
Publication statusPublished - 2022
Event19th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2022 - Los Angeles, United States
Duration: 20 Jun 202223 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13292 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2022
Country/TerritoryUnited States
CityLos Angeles
Period20/06/2223/06/22

Keywords

  • Constraint Programming
  • Hybrid Flowshop
  • Metaheuristics
  • Scheduling

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