Stochastic evolution: a fast effective heuristic for some generic layout problems

Authors:
Youssef G. Saab;Vasant B. Rao
Affiliations:
Coordinated Science Laboratory and Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 1101 W. Springfield Avenue, Urbana, Illinois;Coordinated Science Laboratory and Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 1101 W. Springfield Avenue, Urbana, Illinois
Venue:
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
Year:
1991

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Abstract

There are two canonical optimization problems, namely, NETWORK BISECTIONING (NB) and TRAVELING SALESMAN (TS), that emerge from the physical design and layout of integrated circuits. In this paper, we use an analogy between iterative techniques for combinatorial optimization and the evolution of biological species to obtain the Stochastic Evolution (SE) heuristic for solving a wide range of combinatorial optimization problems. We show that SE can be specifically tailored to solve both NB and TS. Experimental results for the NB and TS problems show that the SE algorithm produces better quality solutions and is faster than the Simulated Annealing algorithm in all instances considered.