Enhanced Simulated Annealing Technique for the Single-Row Routing Problem

This paper presents ESSR (Enhanced Simulated annealing for Single-row Routing) model for solving the single-row routing problem. The main objective in this problem is to produce a realization that minimizes both the street congestion and the number of doglegs. Simulated annealing (SA) is a stochastic, hill-climbing and gradient-descent technique based on the statistical properties of particles undergoing thermal annealing. By performing slow cooling, the nets in the single-row routing problem align themselves according to a configuration with the lowest energy. The model has been known to produce reasonably good solutions for many NP-complete optimization problems, such as the single-row routing problem. In ESSR, our strategy is to minimize both the street congestion and the number of interstreet crossings (doglegs) by expressing a single energy function as their collective properties. This objective is achieved by representing the energy as the absolute sum of the heights of the net segments. To speed up convergence, we pivot the street congestion value while having the energy drops directly proportional to the number of doglegs. This action has the effect of minimizing the number of doglegs as the energy stabilizes. Our simulation work on ESSR produces optimal results in most cases for both the street congestion and the number of doglegs. Our experimental results compare well against results obtained from our earlier model (SRR-7) and two other methods reported in the literature.

[1]  Malgorzata Marek-Sadowska,et al.  An Efficient Single-Row Routing Algorithm , 1984, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[2]  Sartaj Sahni,et al.  Single Row Routing , 1983, IEEE Transactions on Computers.

[3]  Ernest S. Kuh,et al.  On optimum single row routing , 1979 .

[4]  Albert Y. Zomaya,et al.  Scheduling in Parallel Computing Systems , 1999 .

[5]  Emile H. L. Aarts,et al.  Simulated annealing and Boltzmann machines - a stochastic approach to combinatorial optimization and neural computing , 1990, Wiley-Interscience series in discrete mathematics and optimization.

[6]  David Hung-Chang Du,et al.  Heuristic Algorithms for Single Row Routing , 1987, IEEE Transactions on Computers.

[7]  M. Kluger,et al.  Endogenous pyrogen activity in human plasma after exercise. , 1983, Science.

[8]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[9]  Rob A. Rutenbar,et al.  Simulated annealing algorithms: an overview , 1989, IEEE Circuits and Devices Magazine.

[10]  Ehl Emile Aarts,et al.  Simulated annealing and Boltzmann machines , 2003 .

[11]  Albert Y. Zomaya,et al.  A Time- and Cost-Optimal Algorithm for Interlocking Sets-With Applications , 1996, IEEE Trans. Parallel Distributed Syst..

[12]  E. Kuh,et al.  The multilayer routing problem: Algorithms and necessary and sufficient conditions for the single-row, single-layer case , 1976 .