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