An ILS heuristic for the ship scheduling problem: application in the oil industry

DOI10.1111/itor.12610OpenAlexW2899966097WikidataQ128963640 ScholiaQ128963640MaRDI QIDQ6088240

Unnamed Author, Silvio Hamacher, Unnamed Author, Luciana S. Pessoa

Publication date: 16 November 2023

Published in: International Transactions in Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/itor.12610

zbMATH Keywords

metaheuristicsmixed integer linear programmingiterated local searchoil industryship scheduling

Mathematics Subject Classification ID

Operations research, mathematical programming (90-XX)

Related Items (10)

A hybrid iterated local search heuristic for the traveling salesperson problem with hotel selection ⋮ Predictive-reactive strategy for identical parallel machine rescheduling ⋮ A solution framework for the integrated periodic supply vessel planning and port scheduling in oil and gas supply logistics ⋮ The family traveling salesman problem with incompatibility constraints ⋮ A biased‐randomized iterated local search for the distributed assembly permutation flow‐shop problem ⋮ Heuristic approaches for the family traveling salesman problem ⋮ From fitness landscapes evolution to automatic local search algorithm generation ⋮ A solution framework for the integrated periodic supply vessel planning and port scheduling in oil and gas supply logistics ⋮ Matheuristics for a parallel machine scheduling problem with non-anticipatory family setup times: application in the offshore oil and gas industry ⋮ Iterated greedy algorithms for a complex parallel machine scheduling problem

Cites Work

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• A state-of-the-art review of parallel-machine scheduling research
• An iterated local search algorithm for the permutation flowshop problem with total flowtime criterion
• Makespan minimization for two parallel machines scheduling with a periodic availability constraint
• Identical parallel-machine scheduling under availability constraints to minimize the sum of completion times
• Using iterated local search for solving the flow‐shop problem: Parallelization, parametrization, and randomization issues

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