2026-09-19T08:15:09Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/20149 2023-07-10 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Wah, Benjamin W. Chu, Lon-Chan 2011-05-07T12:30:22Z 2011-05-07T12:30:22Z 10000-01-01 1994 The goal of this research is to develop a systematic, integrated method of designing efficient search algorithms that solve optimization problems in real time. Search algorithms studied in this thesis comprise meta-control and primitive search. The class of optimization problems addressed are called combinatorial optimization problems, examples of which include many NP-hard scheduling and planning problems, and problems in operations research and artificial-intelligence applications. The problems we have addressed have a well-defined problem objective and a finite set of well-defined problem constraints. In this research, we use state-space trees as problem representations. The approach we have undertaken in designing efficient search algorithms is an engineering approach and consists of two phases: (a) designing generic search algorithms, and (b) improving by genetics-based machine learning methods parametric heuristics used in the search algorithms designed. Our approach is a systematic method that integrates domain knowledge, search techniques, and automated learning techniques for designing better search algorithms. Knowledge captured in designing one search algorithm can be carried over for designing new ones. Made available in DSpace on 2011-05-07T12:30:22Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9512334.pdf: 14124534 bytes, checksum: cee642ea3a6b6b23734654812568df24 (MD5) Previous issue date: 1994 Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:41:53Z Item is restricted indefinitely. Restriction data tranferred 2014-07-01T11:18:11-05:00 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 AAI9512334 (UMI)AAI9512334 http://hdl.handle.net/2142/20149 eng Copyright 1994 Chu, Lon-Chan Engineering, Electronics and Electrical Artificial Intelligence Computer Science Algorithms for combinatorial optimization in real-time and their automated refinements by genetics-based learning text Electrical and Computer Engineering Electrical Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.