Earticle

초록

영어

Known as an NP-Complete problem, the channel routing problem is very important in the automatic layout design of VLSI circuit and printed circuit boards. A distributed hybrid algorithm for this channel routing problem is presented in MPI environments. This system is implemented on a network of personal computers running Linux operating system connected via 100Mbps Ethernet. Each slave processor generates its own sub-population using genetic operations and communicates with the master processor in an asynchronous manner to form the global population. The proposed hybrid algorithm of Mean Field Annealing and Simulated annealing-like Genetic Algorithm combines the benefit of rapid convergence property of MFA and the effective genetic operations of SGA. The experimental results show that the proposed algorithm maintains the convergence properties of sequential genetic algorithm while it achieves linear speedup as the nets of the channel routing and the number of computing processors increase.

목차

Abstract
 1. Introduction
 2. Genetic Operations for Channel Routing
  2.1 Representation of Chromosome
  2.2 Objective Function
  2.3 Genetic Operators
 3. The Proposed Distributed Algorithm
  3.1 Distributed Mean Field Annealing (MFA)
  3.2 Distributed Simulated Annealing-like Genetic Algorithm (SGA)
  3.3 MGA Hybrid Algorithm
 4. Simulated and Evaluation
 5. Conclusions
 References

키워드

저자

• Chuleui Hong [ Department of Computer Science, Sangmyung University, Seoul, Korea ]
• Yeongjoon Kim [ Department of Computer Science, Sangmyung University, Seoul, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605