DocumentCode :
321255
Title :
Algorithm comparison for manufacturing scheduling problems
Author :
Chen, Chun-Hung ; Wu, S. David ; Dai, Liyi
Author_Institution :
Dept. of Syst. Eng., Pennsylvania Univ., Philadelphia, PA, USA
Volume :
2
fYear :
1997
fDate :
10-12 Dec 1997
Firstpage :
1214
Abstract :
The performance of heuristic algorithms for combinatorial optimization is often highly sensitive to problem instances. A specialized heuristic algorithm may perform exceptionally well on a particular set of instances while fail to produce acceptable solutions on others. This paper proposes a formal method for comparing and selecting heuristic algorithms in real-time given a desired confidence level and a particular set of problem instances. We formulate this algorithm selection problem as a stochastic optimization problem. Two approaches for optimization, ordinal optimization and computing budget allocation, are applied to solve this algorithm selection problem. Computational testing on a set of statistical clustering algorithms in the IMSL library is conducted, which demonstrates that our method can effectively compare and select algorithms that are expected to perform well on given problem instances
Keywords :
heuristic programming; optimisation; pattern recognition; production control; IMSL library; combinatorial optimization; computing budget allocation; heuristic algorithms; manufacturing scheduling problems; ordinal optimization; specialized heuristic algorithm; statistical clustering algorithms; stochastic optimization problem; Clustering algorithms; Computational efficiency; Cost function; Heuristic algorithms; Iterative algorithms; Job shop scheduling; Manufacturing; Scheduling algorithm; Stochastic processes; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
ISSN :
0191-2216
Print_ISBN :
0-7803-4187-2
Type :
conf
DOI :
10.1109/CDC.1997.657617
Filename :
657617
Link To Document :
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