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Abstract(s)
A presente dissertação de mestrado enquadra-se no âmbito dos Sistemas de
Apoio à Decisão para a otimização dos Pontos de Apoio Logísticos Avançados que
servem de armazéns de mercadorias para os navios da esquadra da Marinha de Guerra
de Angolana.
Foram recolhidos dados reais das facilidades de transporte de mercadorias em
Angola, pedidos de transferências de material em Portugal e modelados através de
métodos meta-heurísticos. O principal objetivo da dissertação consiste em minimizar os
custos e as demoras de fornecimento dos materiais necessários para garantir o
funcionamento dos armazéns da Marinha de Guerra de Angolana. Tratando-se dum
problema de programação não-linear, aplicaram-se os métodos do Algoritmo Genético e
Simulated Annealing para obter o menor valor da solução.
O menor valor da solução é obtido a partir dum processo de simulação através
na ferramenta informática Matlab, onde o utilizador poderá alterar os valores de entrada
consoante o grau de importância das variáveis de decisão (custo e demora).
Os resultados obtidos em ambos métodos variaram significativamente consoante
as alterações feitas pelo decisor durante o processo de simulação para 60 meses. Estes
resultados apontaram o Simulated Annealing como melhor método heurístico para a
resolução de problemas de esfera idêntica.
This dissertation deals with a type of Decision Support Systems for the optimization of Points Advanced Logistic Support serving warehouse goods for ships of the squadron of the Navy of Angolan. Data were collected from actual freight facilities in Mozambique, requests for material transfers in Portugal and modeled by meta-heuristic methods. The main objective of the dissertation is to minimize costs and delays in the provision of materials necessary to ensure the functioning of the warehouses of the Navy of Angolan. For this case there is a problem of nonlinear programming, we applied the methods of genetic algorithm and simulated annealing to obtain the lowest value of the solution. The lowest value of the solution is obtained from a process through simulation in Matlab software tool, where the user can change the input values depending on the degree of importance of decision variables (cost and delay). The results obtained by both methods varied significantly depending on the changes made by the decision maker during simulation process for 60 months. Those results show that the Simulated Annealing heuristic as the best method for solving problems similar sphere.
This dissertation deals with a type of Decision Support Systems for the optimization of Points Advanced Logistic Support serving warehouse goods for ships of the squadron of the Navy of Angolan. Data were collected from actual freight facilities in Mozambique, requests for material transfers in Portugal and modeled by meta-heuristic methods. The main objective of the dissertation is to minimize costs and delays in the provision of materials necessary to ensure the functioning of the warehouses of the Navy of Angolan. For this case there is a problem of nonlinear programming, we applied the methods of genetic algorithm and simulated annealing to obtain the lowest value of the solution. The lowest value of the solution is obtained from a process through simulation in Matlab software tool, where the user can change the input values depending on the degree of importance of decision variables (cost and delay). The results obtained by both methods varied significantly depending on the changes made by the decision maker during simulation process for 60 months. Those results show that the Simulated Annealing heuristic as the best method for solving problems similar sphere.
Description
Keywords
Algoritmo Genético, Simulated Annealing, Custos, Demoras, Transporte. Genetic Algorithm, Simulated Annealing, Costs, Delays, Transportation