Mémoire de Maîtrise
DOI
https://doi.org/10.11606/D.3.2021.tde-18012022-124410
Document
Auteur
Nom complet
Fabio Gasparotto Boaventura
Unité de l'USP
Domain de Connaissance
Date de Soutenance
Editeur
São Paulo, 2021
Directeur
Jury
Mendes, André Bergsten (Président)
Brinati, Marco Antonio
Rangel, Maria do Socorro Nogueira
Titre en portugais
Uma abordagem matheuristic para o problema de alocação de cargas no convés de navios de apoio offshore.
Mots-clés en portugais
Otimização combinatória
Otimização linear e não linear
Otimização matemática
Problema da mochila bidimensional
Problemas de corte e empacotamento
Programação matemática
Resumé en portugais
Titre en anglais
A matheuristic approach to the cargo allocation problem on the main deck of offshore supply vessels.
Mots-clés en anglais
Combinatorial optimization
Cutting and packing problems
Linear and non-linear optimization
Mathematical modeling
Two-dimensional knapsack problem
Resumé en anglais
This dissertation presents a matheuristic approach for the problem of general cargo allocation on the deck of platform supply vessels with multiple deliveries. An operational characteristic found in activities to support oil exploration is that a single vessel, usually, should take supplies to more than one offshore unit. In addition to the classic constraints of non-overlapping loads and that all loads must be fully contained within the vessel, the following constraints are added: sets of loads with certain characteristics must remain nearby or grouped (e.g., same destination); dangerous goods have a predetermined area on the vessel`s main deck; there are reserved areas which should be free of cargo; the number of refrigerated loads is bounded by the number of power outlets on the ship's deck; and there are cargoes that must be loaded. All these impositions constitute the problem herein studied. The objective is to maximize the sum of the priorities (value) of the loaded cargoes. This problem is a variation of the classic two-dimensional knapsack problem, which is NP-hard. This work proposes to solve instances originated from real data and, therefore, with practical and real-scale applications, through a matheuristic approach with three stages, which uses linear and non-linear mathematical programming models on its solution.

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Date de Publication
2022-01-18

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