Synthesizing a predatory search strategy for VLSI layouts

When searching for prey, many predator species exhibit a remarkable behavior: after prey capture, the predators promptly engage in ‘area-restricted search’, probing for consecutive captures nearby. Biologists have been surprised with the efficiency and adaptability of this search strategy to a great number of habitats and prey distributions. We propose to synthesize a similar search strategy for the massively multimodal problems of combinatorial optimization. The predatory search strategy restricts the search to a small area after each new improving solution is found. Subsequent improvements are often found during area-restricted search. Results of this approach to Gate Matrix Layout, an important problem arising in VLSI architectures, are presented. Compared to established methods over a set of benchmark circuits, predatory search is able to either match or outperform the best known layouts. Additional remarks address the relation of predatory search to the ‘big-valley’ hypothesis and to the field of Artificial Life. Index Terms Predatory Search, Adaptive Behavior, VLSI Layout, Combinatorial Optimization, ‘big-valley’ Hypothesis. This work has been submitted to the IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION for possible publication. Copyright may be transferred without notice, after which this version will be superseded.