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Artificial intelligence in highway l...

Kang, Min-Wook.

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Artificial intelligence in highway location and alignment optimization = applications of genetic algorithms in searching, evaluating, and optimizing highway location and alignments /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial intelligence in highway location and alignment optimization/ Min-Wook Kang, Paul Schonfeld.
其他題名:	applications of genetic algorithms in searching, evaluating, and optimizing highway location and alignments /
作者:	Kang, Min-Wook.
其他作者:	Schonfeld, Paul.
出版者:	Singapore :World Scientific, : c2021.,
面頁冊數:	1 online resource (xii, 276 p.)
內容註:	About 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.
標題:	Roads - Design and construction -
電子資源:	https://www.worldscientific.com/worldscibooks/10.1142/11059#t=toc
ISBN:	9789813272811

Artificial intelligence in highway location and alignment optimization = applications of genetic algorithms in searching, evaluating, and optimizing highway location and alignments /
Kang, Min-Wook.

Artificial intelligence in highway location and alignment optimizationapplications of genetic algorithms in searching, evaluating, and optimizing highway location and alignments /[electronic resource] :Min-Wook Kang, Paul Schonfeld. - 1st ed. - Singapore :World Scientific,c2021. - 1 online resource (xii, 276 p.)

Includes bibliographical references and index.

About 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.

"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.

Mode of access: World Wide Web.

ISBN: 9789813272811Subjects--Topical Terms:

3512706
Roads
--Design and construction

LC Class. No.: TE175 / .K25 2021

Dewey Class. No.: 625.725028563

Artificial intelligence in highway location and alignment optimization = applications of genetic algorithms in searching, evaluating, and optimizing highway location and alignments /
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260 $a Singapore : $b World Scientific, $c c2021.
300 $a 1 online resource (xii, 276 p.)
504 $a Includes bibliographical references and index.
505 0 $a About 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 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat Reader.
588 $a Description based on print version record.
650 0 $a Roads $x Design and construction $x Mathematical models. $3 3512706
650 0 $a Highway planning $x Mathematical models. $3 3512707
650 0 $a Genetic algorithms. $3 533907
650 0 $a Artificial intelligence $x Engineering applications. $3 1567162
650 0 $a Mathematical optimization. $3 517763
700 1 $a Schonfeld, Paul. $3 3512705
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/11059#t=toc