Name: Marcos Daniel Valadão Baroni
Type: PhD thesis
Publication date: 31/07/2018
Advisor:

Namesort descending Role
Flávio Miguel Varejão Advisor *

Examining board:

Namesort descending Role
ALEXANDRE LOUREIROS RODRIGUES External Examiner *
Flávio Miguel Varejão Advisor *
Maria Claudia Silva Boeres Internal Examiner *
Simone de Lima Martins External Examiner *
Thomas Walter Rauber Internal Examiner *

Summary: Several real problems involve the simultaneous optimization of multiple criteria, which are generally conflicting with each other. These problems are called multiobjective and do not have a single solution, but a set of solutions of interest, called efficient solutions or non-dominated solutions. One of the great challenges to be faced in solving this type
of problem is the size of the solution set, which tends to grow rapidly given the size of the instance, degrading algorithms performance. Among the most studied multiobjective problems is the multiobjective knapsack problem, by which several real problems can be modeled. This work proposes the acceleration of the resolution process of the multiobjective
knapsack problem, through the use of a k-d tree as a multidimensional index structure to assist the manipulation of solutions. The performance of the approach is analyzed through computational experiments, performed in the exact context using a state-of-the-art
algorithm. Tests are also performed in the heuristic context, using the adaptation of ametaheuristic for the problem in question, being also a contribution of the present work. According to the results, the proposal was effective for the exact context, presenting a speedup up to 2.3 for bi-objective cases and 15.5 for 3-objective cases, but not effective in the heuristic context, presenting little impact on computational time. In all cases, however,there was a considerable reduction in the number of solutions evaluations.

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