Abstract
The paper addresses the problem of assigning robots to target locations in the context of a disaster management scenario, while minimizing a set of pre-defined objectives. The problem is formulated as a Multi-objective Multiple Traveling Salesman Problem. A three-phase mechanism based on Analytical Hierarchy Process (AHP) is proposed. In the first phase, AHP is used to systematically define weights for each objective. In the second phase, the robots contend for the allocation of available targets using three different approaches. In the third phase, an improvement phase is carried out to refine the targets' allocation. A Matlab simulation studies is used to examine the performance of the proposed solutions with three objective functions namely the total traveled distance, the maximum tour and the deviation rate. The comparison between the three proposed approaches shows that, for large scenario, the marketbased approach gives the best solution over the RTMA and the Balanced approach. Moreover, the comparison of the proposed multi-objective approach with the mono-objective one shows that our proposed approach outperforms the mono-objective one in the global cost when considering the three objectives. A slightly additional cost in the specific objective is considered in the monoobjective approach.