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Automatic Generation of Heuristics for SchedulingThis paper presents a technique, called GenH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing consensus that heuristics encode advice that is, at best, useful in solving most, or typical, problem instances, and, at worst, useful in solving only a narrowly defined set of instances. In either case, heuristic problem solvers, to be broadly applicable, should have a means of automatically adjusting to the idiosyncrasies of each problem instance. GenH generates a search heuristic for a given problem instance by hill-climbing in the space of possible multi-attribute heuristics, where the evaluation of a candidate heuristic is based on the quality of the solution found under its guidance. We present empirical results obtained by applying GenH to the real world problem of telescope observation scheduling. These results demonstrate that GenH is a simple and effective way of improving the performance of an heuristic scheduler.
Document ID
20020043146
Document Type
Conference Paper
Authors
Morris, Robert A. (Florida Inst. of Tech. FL United States)
Bresina, John L. (RECOM Technologies, Inc. United States)
Rodgers, Stuart M. (University of West Florida Pensacola, FL United States)
Date Acquired
August 20, 2013
Publication Date
January 1, 1997
Subject Category
Cybernetics, Artificial Intelligence and Robotics
Meeting Information
Fifteenth International Joint Conference on Artificial Intelligence(Nagoya)
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.