Decision making in VLSI components placement problem based on grey wolf optimization

• Published in: East-West Design and Test Symposium pp. 1 - 4
• Main Authors: Kuliev, Elmar V., Kureichik, Vladimir Vl, Kursitys, Ilona O.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2019
• Subjects: Biological cells; Design automation; genetic algorithm; Mathematical model; neighborhood; objective function; Optimization; swarm intelligence; Task analysis; Time complexity; Very large scale integration; wolf pack
• ISSN: 2472-761X
• DOI: 10.1109/EWDTS.2019.8884371

This article is devoted to one of the key automated design tasks, which is the problem of the VLSI components placement. The possibilities of bioinspired algorithms development and application for the purpose of the effective decision support in the CAD sphere are of a great interest today. With that, there is a constant conflict between the CAD complexity and requirements of the effective decision support in real time. Such methods as parallelizing of the decision support process, increasing the number of operators or users are not able to solve the tasks mentioned above completely. The paper considers the new technologies combining computer science, bionics and computer-aided design as the way to solve this problem. In this context, the development of the new principles and methods of effective decision support in design and management problems is of a great economic and social importance and is claimed to be relevant today. The paper describes the living nature algorithm based on the grey wolf pack behavior. The authors formulate the problem of the VLSI components placement on a set of positions of a discrete work field. The modified technology of the bioinspired algorithms development and the main steps of the grey wolf pack behavior in terms of the VLSI placement problem are presented in the paper. The computational experiments show the results of the developed approach. The main purpose of the research is to estimate the possibilities of integrated nature-inspired methods for the purpose of CAD problems solving based on the grey wolf pack behavior in wildlife.