This paper proposes a hybrid heuristic algorithm, based on the metaheuristics Greedy Randomized Adaptive Search Procedure, Iterated Local Search and Variable Neighborhood Descent, to solve the Clustered Traveling Salesman Problem (CTSP). Hybrid Heuristic algorithm uses several variable neighborhood structures combining the intensification (using local search operators) and diversification (constructive heuristic and perturbation routine). In the CTSP, the vertices are partitioned into clusters and all vertices of each cluster have to be visited contiguously. The CTSP is N P-hard since it includes the well-known Traveling Salesman Problem (TSP) as a special case. Our hybrid heuristic is compared with three heuristics from the literature and an exact method. Computational experiments are reported for different classes of instances. Experimental results show that the proposed hybrid heuristic obtains competitive results within reasonable computational time.
Resumo: O Problema do Caixeiro Viajante com Grupamentos (PCVG) é uma generalização do Problema do Caixeiro Viajante (PCV) em que o conjunto de vértices é particionado em grupos disjuntos e o objetivo é encontrar um ciclo Hamiltoniano de custo mínimo tal que os vértices em cada grupo são visitados na forma contígua. O PCVG é NP-difícil e nesse contexto são propostos métodos heurísticos para o PCVG usando GRASP, Reconexão de Caminhos e Método de Descida em Vizinhança Variável (MDVV). Os métodos heurísticos foram testados usando instancias Euclidianas com até 2000 vértices e grupos variando entre 4 a 15 vértices. Os testes computacionais foram executados para comparar o desempenho dos métodos heurísticos com um algoritmo exato usando o software CPLEX Paralelo. Os resultados computacionais mostraram que o método heurístico híbrido usando MDVV sobressaiu em relação aos outros métodos.
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