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Rao, Vasant B. Saab, Youssef Georges 2011-05-07T12:15:35Z 2011-05-07T12:15:35Z 10000-01-01 1990 In this thesis, a new general adaptive algorithm for solving a wide variety of NP-Complete combinatorial problems is developed. The new technique is called Stochastic Evolution (SE). The SE algorithm is applied to Network Bisection, Vertex Cover, Set Partition, Hamilton Circuit, Traveling Salesman, Linear Ordering, Standard Cell Placement, and Multi-way Circuit Partitioning problems. It is empirically shown that SE out-performs the more established general optimization algorithm, namely, Simulated Annealing. Made available in DSpace on 2011-05-07T12:15:35Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9114396.pdf: 3854467 bytes, checksum: 6db5947c8446ada4827f2b78240de1d4 (MD5) Previous issue date: 1990 Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:38:48Z Item is restricted indefinitely. Restriction data tranferred 2014-07-01T11:16:14-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission ETDs are only available to UIUC Users without author permission U of I Only AAI9114396 (UMI)AAI9114396 http://hdl.handle.net/2142/19695 eng Copyright 1990 Saab, Youssef Georges Engineering, Electronics and Electrical Computer Science Combinatorial optimization by stochastic evolution with applications to the physical design of VLSI circuits text Electrical and Computer Engineering Electrical and Computer Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.