The travelling maintainer problem: integration of condition-based maintenance with the travelling salesman problem

The Travelling Salesman Problem (TSP) is one of the most studied problems in the literature due to its applicability to a large number of real cases. Most variants of the TSP consider total distance travelled. This paper presents a new generalised formulation of the TSP that aims to minimise the sum of functions of latencies to cities, rather than total distance travelled. Then, a new problem that uses a special function using the latency as input is presented, called the Travelling Maintainer Problem (TMP). The TMP integrates the output of prognostics in Condition-based Maintenance (CBM) with the TSP. CBM aims to minimise the failure and maintenance cost by identifying and predicting upcoming failures through the analysis of sensory information collected in real-time. Maintenance scheduling is performed using the predicted failure information obtained from the CBM. When the systems to be maintained are geographically distributed, maintenance scheduling requires integrated analysis of travel times and their effects on the failure progression in systems. This paper also presents Genetic Algorithm and Particle Swarm Optimisation-based solutions and their comparisons for the TMP on a case study.