Tabu Search metaheuristic embedded in Adaptative Memory Procedure for the Profitable Arc Tour Problem

In this paper we propose a tabu search heuristic embedded in adaptative memory procedure to solve the Profitable Arc Tour Problem (PATP). The PATP is a variant of the well-known Vehicle Routing Problem in which a set of vehicle tours are constructed. The objective is to find a set of cycles in the tours of vehicle that maximize the collection of profits minus travel costs, which is in its turn subject to constraints limiting the length of cycles that profit is available on arcs.. Computational experiments show that our algorithm provides better solutions in terms quality of solution and completion processing times.