Clonal Selection Algorithm for the Team Orienteering Problem

This paper describes how a new solution approach based on the clonal selection algorithm is operating for solving the team orienteering problem (TOP) which is a generalization of the well-known vehicle routing problems. The objective is to maximize the profit gained from visiting customers without exceeding a travel time limit. This algorithm introduces theories of clonal selection, hypermutation and receptor edit to construct an evolutionary searching mechanism which is applied for exploration. A local search mechanism is integrated to exploit local optima. In order to demonstrate the effectiveness of the proposed algorithm, most widely used benchmark problems are solved and the obtained results are compared with different methods collected from the literature. The results demonstrate that the proposed algorithm is a very effective and performs well on all test problems.