J Sched (2006) 9:469–491 DOI 10.1007/s10951-006-8596-4 A case study of mutual routing-scheduling reformulation ∗ J. Christopher Beck · Patrick Prosser · Evgeny Selensky C  Springer Science + Business Media, LLC 2006 Abstract Classical models of combinatorial problems, such as scheduling, play a key role in optimization research as they allow theoretical and empirical work to focus on core issues of problem solving performance. By their very nature, however, classical models are a simplifi- cation of real-world problems. We argue that the challenge now is to address those real-world features that were simplified away in the classical models, and that in order to do this we should investigate how problem features affect solution technologies. In this paper, we per- form an empirical study of vehicle routing problems (VRPs) and job shop scheduling problems (JSPs) using commercially available constraint-based optimization software, ILOG Dispatcher, and ILOG Scheduler. We start with instances of the classical VRP and JSP and systemati- cally make the two problems more realistic by removing the simplifying assumptions of the classical models. While doing so, we empirically investigate the key problem characteristics that make the problems more amenable to one solution technique or the other. We[-5pc] argue that our observations are symptomatic of the underlying technologies used in the employed software. Keywords job shop scheduling, vehicle routing, problem reformulation, empirical analysis ∗ This work was supported by EPSRC research grant GR/M90641, by Science Foundation Ireland under Grant 00/PI.1/C075, and by ILOG, SA. J. C. Beck () Department of Mechanical & Industrial Engineering, University of Toronto, Canada e-mail: jcb@mie.utoronto.ca P. Prosser Department of Computing Science, University of Glasgow, Scotland e-mail: pat@dcs.gla.ac.uk E. Selensky Vidus Limited, Ipswich, Suffolk, UK e-mail: eselensky@vidus.com