Key-node-based local search discrete artificial bee colony algorithm for obstacle-avoiding rectilinear Steiner tree construction

Abstract

The obstacle-avoiding rectilinear Steiner minimal tree (OARSMT) problem is a fundamental problem in very large-scale integrated circuit physical design and can be reduced to the Steiner tree problem in graphs (GSTP), which can be solved by using three types of common methods: classic heuristics, local search algorithms, or computational intelligence algorithms. However, classic heuristics have poor solution qualities; local search algorithms easily fall into the problem of the local optimum; and the searching effects of the existing computational intelligence algorithms are poor for this problem. In order to improve the solution quality, we propose a novel discrete artificial bee colony algorithm for constructing an obstacle-avoiding rectilinear Steiner tree. We first generate the escape graph for the OARSMT problem. Then, we search for a near-optimal solution consisting of some edges of escape graph by using the discrete ABC algorithm. We apply a key-node neighborhood configuration for the local search strategy and introduce two local search operators. We then naturally use a key-node-based encoding scheme for representing the feasible solution and obtain a tight searching scope. We employ a modified classic heuristic as the encoder that can produce a feasible solution. Experiments conducted on both general GSTP and very large-scale integrated circuit instances reveal the superior performance of the proposed method in terms of the solution quality among the state-of-the-art algorithms.