<XML><RECORDS><RECORD><REFERENCE_TYPE>0</REFERENCE_TYPE><REFNUM>8570</REFNUM><AUTHORS><AUTHOR>Brind,C.</AUTHOR><AUTHOR>Muller,C.</AUTHOR><AUTHOR>Prosser,P.</AUTHOR></AUTHORS><YEAR>1995</YEAR><TITLE>Stochastic techniques for resource management</TITLE><PLACE_PUBLISHED>BT technology journal</PLACE_PUBLISHED><PUBLISHER>N/A</PUBLISHER><PAGES>55-63</PAGES><ISBN>1358-3948</ISBN><LABEL>Brind:1995:8570</LABEL><KEYWORDS><KEYWORD>stochastic search</KEYWORD></KEYWORDS<ABSTRACT>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</ABSTRACT></RECORD></RECORDS></XML>