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An Adaptive Tabu Search (ATS) and Other Metaheuristics for a Class of Optimal Allocation Problems
Shigeyuki Takahara* and Sadaaki Miyamoto*
*Kagawa Prefectural Industrial Technology Center
587-1 Goto-cho Takamatsu Kagawa 761-8031, Japan
**Institute of Information Sciences and Electronics, University of Tsukuba Ibaraki 305-8573, Japan
Received:July 9, 1998Accepted:September 18, 1998Published:February 20, 1999
Keywords:Combinatorial optimization, Adaptive tabu search nesting problem, Metaheuristics, CAD
Abstract
We propose an ATS, for a class of optimal allocation problems, that uses various types of memory to make the search effective. To improve efficiency, our tabu search (TS) uses a combination of objects, rather than moves, as memory elements, simplifying search constraints and improving search efficiency. The ATS is applied to optimal allocation of irregular shapes on a sheet to minimize waste. The effectiveness of the proposed method is compared to other metaheuristics in a simulation whose results show the ATS to be superior.
Cite this article as:S. Takahara and S. Miyamoto, “An Adaptive Tabu Search (ATS) and Other Metaheuristics for a Class of Optimal Allocation Problems,” J. Adv. Comput. Intell. Intell. Inform., Vol.3 No.1, pp. 21-27, 1999.Data files:
