CSM-210 page - 1 An Attempt to Map the Performance of a Range of Algorithm and Heuristic Combinations * Edward P. K. Tsang, James E. Borrett, & Alvin C. M. Kwan {edward, jborrett, alvin}@essex.ac.uk Department of Computer Science University of Essex Wivenhoe Park Colchester CO4 3SQ United Kingdom tel: 0206 872774 September 1994 Abstract Constraint satisfaction is the core of many AI and real life problems and much research has been done in this field in recent years. Work has been done in the past in comparing the performance of different algorithms and heuristics. Much of such work has focused on finding "the best" algorithm and heuristic combination for all problems. The objective of this paper is to prove that there is no universally best algorithm and heuristic for all problems -- different problems can be solved most efficiently by different algorithm and heuristic combinations. The implication of this is important because it means that instead of trying to find "the best" algorithms and heuristics, future research should try to identify the application domain of each algorithm and heuristic (i.e. when they are most effective). Furthermore our results point to future research which focuses on how to retrieve the most efficient algorithm for a given problem. The results in this paper provide a first step towards achieving such goals. * The research reported in this paper was supported by the University of Essex research promotion fund ref. R7027 and by the EPSRC research grant ref. GR/J/42878.