Stochastic techniques for resource management

This paper investigates a number of stochastic search techniques applied to vehicle routeing problems (VRPs) with time-windows and technological constraints. Five techniques are investigated ― genetic algorithms (GA), hill-climbing (HC), random search (RS), simulated annealing (SA), and tabu search (TS). Their performance is examined and compared over a wide range of VRPs with varying degrees of workforce specialisation, job time-windows and personnel resources. The objective of the study is twofold ― firstly, to examine the behaviour of the techniques and to identify the best, and secondly to examine features of the problem in such a way that the behaviour of the techniques and possibly the quality of the solutions can be anticipated