DocumentCode :
2362354
Title :
Job sequencing with quadratic penalties: An A*-based graph search approach
Author :
Sen, Anup K. ; Bagchi, Amitava
Author_Institution :
Sch. of Ind. Manage., New Jersey Inst. of Technol., Newark, NJ, USA
fYear :
1993
fDate :
1-5 Mar 1993
Firstpage :
190
Lastpage :
196
Abstract :
The authors tried to establish that A* is much better than traditional branch-and-bound procedures at solving certain types of minimum-penalty job-sequencing problems. Townsend´s algorithm (1976) for minimum-penalty job sequencing on one machine with quadratic penalties was implemented both as tree search and as a graph-based A* formation that uses Townsend´s lower bounds at nodes as heuristic estimates. The graph implementation took much less time to run, and problem instances of much larger size could be solved. The approach seems to be particularly suitable for sequencing and other optimization problems where lower bounds at nodes can be determined without excessive computational effort
Keywords :
graph theory; heuristic programming; optimisation; problem solving; search problems; trees (mathematics); A*; branch-and-bound procedures; computational effort; graph-based A* formation; heuristic estimates; minimum-penalty job-sequencing problem; optimization problems; problem solving; quadratic penalties; tree search; Artificial intelligence; Cities and towns; Electronic mail; Explosions; Operations research; Search methods; Technology management; Traveling salesman problems; Tree graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence for Applications, 1993. Proceedings., Ninth Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-8186-3840-0
Type :
conf
DOI :
10.1109/CAIA.1993.366611
Filename :
366611
Link To Document :
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