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040 _a WSPC
_b eng
_c WSPC
010 _z 2019057609
020 _a9789813272811
_q(ebook)
020 _z9789813272804
_q(hbk.)
050 0 4 _aTE175
_b.K25 2020
072 7 _aTEC
_x009140
_2bisacsh
072 7 _aCOM
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072 7 _aTRA
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082 0 4 _a625.725028563
_223
100 1 _aKang, Min-Wook.
_9178580
245 1 0 _aArtificial intelligence in highway location and alignment optimization
_h[electronic resource] :
_bapplications of genetic algorithms in searching, evaluating, and optimizing highway location and alignments /
_cby Min-Wook Kang, Paul Schonfeld.
260 _aSingapore :
_bWorld Scientific,
_c2020.
300 _a1 online resource (xii, 276 p.)
504 _aIncludes bibliographical references and index.
505 0 _aAbout the authors -- Overview of highway location and alignment optimization problem. Introduction. Highway cost and constraints. Review of artificial intelligence-based models for optimizing highway location and alignment design -- Highway alignment optimization with genetic algorithms. Modeling highway alignments with GAs. Highway alignment optimization formulation. Constraint handling for evolutionary algorithms. Highway alignment optimization through feasible gates. Prescreening and repairing in highway alignment optimization -- Optimizing Simple highway networks : an extension of genetic algorithms-based highway alignment optimization. Overview of discrete network design problems. Bi-level highway alignment optimization within a small highway network. Bi-level HAO model application example -- Highway alignment optimization model applications and extensions. HAO Model application in maryland brookeville bypass project. HAO model application in US 220 project in Maryland. HAO model application to Maryland ICC project. Related developments and extensions -- Appendices. Notation used in the monograph. Traffic inputs to the HAO model for the icc case study -- References -- Index.
520 _a"This monograph provides a comprehensive overview of methods for searching, evaluating, and optimizing highway location and alignments using genetic algorithms (GAs), a powerful Artificial Intelligence (AI) technique. It presents a two-level programming structure to deal with the effects of varying highway location on traffic level changes in surrounding road networks within the highway location search and alignment optimization process. In addition, the proposed method evaluates environmental impacts as well as all relevant highway costs associated with its construction, operation, and maintenance. The monograph first covers various search methods, relevant cost functions, constraints, computational efficiency, and solution quality issues arising from optimizing the highway alignment optimization (HAO) problem. It then focuses on applications of a special-purpose GA in the HAO problem where numerous highway alignments are generated and evaluated, and finally the best ones are selected based on costs, traffic impacts, safety, energy, and environmental considerations. A review of other promising optimization methods for the HAO problem is also provided in this monograph"--Publisher's website.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader.
650 0 _aRoads
_xDesign and construction
_xMathematical models.
_9178581
650 0 _aHighway planning
_xMathematical models.
_9178582
650 0 _aGenetic algorithms.
_93938
650 0 _aArtificial intelligence
_xEngineering applications.
_99193
650 0 _aMathematical optimization.
_94112
655 0 _aElectronic books.
_93294
700 1 _aSchonfeld, Paul.
_9178583
856 4 0 _uhttps://www.worldscientific.com/worldscibooks/10.1142/11059#t=toc
_zAccess to full text is restricted to subscribers.
942 _cEBK
999 _c97833
_d97833