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Master's Dissertation
DOI
https://doi.org/10.11606/D.3.2016.tde-07032016-115426
Document
Author
Full name
Thabiani Cristine Aradi
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2015
Supervisor
Committee
Mendes, André Bergsten (President)
Brinati, Marco Antonio
Seixas, Michel Povlovitsch
Title in Portuguese
Planejamento de operações de manutenção submarina.
Keywords in Portuguese
Heurísticas
Manutenção submarina
Modelagem matemática
Otimização
Simulação
Abstract in Portuguese
A presente pesquisa buscou resolver o problema de planejamento de operações submarinas através das perspectivas de programação de tarefas e dimensionamento de frota. O problema consistiu em estabelecer a melhor sequência de tarefas a serem atendidas por embarcações levando em consideração sua compatibilidade, regras de sequenciamento e o tamanho da frota. O problema é uma extensão do modelo clássico de roteirização com janelas de tempo com o objetivo de minimizar os custos associados à roteirização e as perdas econômicas associadas às interrupções de produção. A resolução do trabalho concentrou-se no curto e longo prazo, utilizando como principal método de solução a heurística Simulated Anneling por meio de um algoritmo de simulação-otimização.
Title in English
Planning problem of offshore maintenance.
Keywords in English
Heuristics
Mathematical modelling
Optimization
Simulation
Undersea maintenance
Abstract in English
This research aimed at solving the problem of planning underwater operations that involves job scheduling and fleet sizing decisions. The problem consisted in establish the best sequence of tasks to be atended by vessels taking into account compatibility constraints, sequencing rules and the size of the fleet. The problem is an extension of the classical vehicle routing problem with time windows. The objective is to minimize the routing costs and the economic losses associated with production losses. The solution procedure focused on short and long-term decisions based on the heuristic Simulated Anneling through a simulation-optimization algorithm.
 
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Publishing Date
2016-03-14
 
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