A practical and efficient approach to the constrained via minimization problem
This paper presents an efficient and practical approach to the Constrained Via Minimization (CVM) problem, which assigns wire segments to the layers, using the minimum number of vias, given a feasible partial routing. The feasible partial routing is first represented by a directed bipartite graph to reflect the mutual constraints. An energy function is then proposed to turn the problem into a cost optimization problem. An efficient heuristic algorithm, combining hill-climbing and simulated annealing, is developed for the cost optimization. The algorithm has the capability to escape from the local minimums and eventually reaches a near-optimal or optimal solution. The proposed method is practical as it can handle many practical constraints such as a multi-way wire split from a single via, and pre-allocation of power nets and terminals. Experimental results show that our proposed method is efficient in handling complex grid-based routing.
Impact and interest:
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Journal Article|
|Additional Information:||For more information, please refer to the journal's website (see hypertext link) or contact the author. Author contact details: firstname.lastname@example.org|
|Keywords:||Constrained via minimization, Topological via minimization, Layer assignment problem, Heuristic algorithm, Cost optimization|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Microelectronics and Integrated Circuits (090604)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Artificial Intelligence and Image Processing not elsewhere classified (080199)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2001 Elsevier|
|Deposited On:||16 Jul 2007|
|Last Modified:||15 Jan 2009 17:38|
Repository Staff Only: item control page