Self-organizing map for orienteering problem with dubins vehicle

Abstract

This paper reports on the application of the self-organizing map (SOM) to solve a novel generalization of the Orienteering Problem (OP) for curvature-constrained vehicles that is called the Dubins Orienteering Problem (DOP). Having a set of target locations, each with associated reward, and a given travel budget, the problem is to find the most valuable curvature-constrained path connecting the target locations such that the path does not exceed the travel budget. The proposed approach is based on two existing SOM-based approaches to solving the OP and Dubins Traveling Salesman Problem (Dubins TSP) that are further generalized to provide a solution of the more computational challenging DOP. DOP combines challenges of the combinatorial optimization of the OP and TSP to determine a subset of the most valuable targets and the optimal sequence of the waypoints to collect rewards of the targets together with the continuous optimization of determining headings of Dubins vehicle at the waypoints such that the total length of the curvature-constrained path is shorter than the given travel budget and the total sum of the collected rewards is maximized.