Marcilene de Fátima Dianin Vianna

Local search-based heuristics for the multiobjective multidimensional knapsack problem

In real optimization problems it is generally desirable to optimize more than one performance criterion (or objective) at the same time. The goal of the multiobjective combinatorial optimization (MOCO) is to optimize simultaneously r > 1 objectives. As in the single-objective case, the use of heuristic/metaheuristic techniques seems to be the most promising approach to MOCO problems because of their efficiency, generality and relative simplicity of implementation. In this work, we develop algorithms based on Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Local Search (ILS) metaheuristics for the multiobjective knapsack problem. Computational experiments on benchmark instances show that the proposed algorithms are very robust and outperform other heuristics in terms of solution quality and running times.

Hybrid GRASP heuristics for the phylogeny problem combining path-relinking and genetic algorithm as an intensification strategy

A phylogeny is a tree that relates taxonomic units based on their similarity over a set of characteristics. The phylogeny problem under the parsimony criterion consists in finding a phylogeny with a minimum number of evolutionary steps. We propose hybrid heuristic methods – based on GRASP, path-relinking and genetic algorithm methodologies – to build a phylogeny while minimizing parsimony. Computational experiments using benchmark conditions are reported, and the results obtained by the proposed hybrid heuristics are compared with the solutions obtained by a traditional GRASP (without hybridization) heuristic and with previously reported solutions in the literature. The experimental results illustrate that the proposed heuristics are efficient in terms of solution quality and time-to-target-value.

GRASP heuristic for p-median problem applied to the location of concentrators

Várias situações práticas reais, tais como localizações de depósitos, hospitais e dispositivos de telecomu-nicações (concentradores, torres de celulares, etc), podem ser vistas como um problema de p-medianas. Este trabalho apresenta uma proposta para a solução do problema de p-medianas baseado no backbone da rede de computadores que será instalado no Instituto Federal Fluminense (IFF). Esse tipo de ocorrência é conhecida na literatura como problema de localização de concentradores. Para resolver a questão citada foi proposta uma heurística GRASP. Testes computacionais realizados, mostram que a heurística elaborada neste trabalho atingiu resultados satisfatórios.

Heurística GRASP para o problema de p-medianas aplicado à localização de concentradores

Several real practical situations, such as location of depots, hospitals and telecommunications devices (hubs, cellular towers, etc.), can be seen as a p-median problem. This paper presents a proposal for solving the p-median problem based on the backbone network of computers that will be installed at the Federal Fluminense Institute (IFF). This type of problem is known in literature as a problem of locating concentrators. To solve the problem cited was proposed a GRASP heuristic. Computational tests performed show that the heuristic developed in this work has reached satisfactory results.