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Multi-objective Optimization for Bus Network Design Problem Using Pareto Optimal : 파레토최적해를 이용한 버스네트워크 설계 다목적 최적화

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dc.contributor.advisor고승영-
dc.contributor.author박수진-
dc.date.accessioned2020-10-13T02:35:29Z-
dc.date.available2020-10-13T02:35:29Z-
dc.date.issued2020-
dc.identifier.other000000163243-
dc.identifier.urihttps://hdl.handle.net/10371/169099-
dc.identifier.urihttp://dcollection.snu.ac.kr/common/orgView/000000163243ko_KR
dc.description학위논문 (박사) -- 서울대학교 대학원 : 공과대학 건설환경공학부, 2020. 8. 고승영.-
dc.description.abstractPublic transportation is a service that provides access to
various opportunities and can reduce the mobility gap through
efficient network design. However, services are concentrated in
a specific area considering economic efficiency, resulting in
spatial imbalances in services and inefficiency to users.
In this study, bus network design algorithms were presented,
including operators, users, and public aspects. An efficiency of
operators and users and the competitiveness of public
transportation between modes and areas were considered. Toy
network was organized according to the urban network
topology and demand pattern, and the analysis was performed
by applying the algorithm of this study. The applicability of the
algorithm was confirmed through the actual network.
An improved network could be derived from both operators and
the public compared to previous research focused on operational
efficiency. Suggested a method to select and apply Pareto
optimal according to the planner's judgment. The bus network
design algorithm in this study can be used as a means of
decision criteria and it can be applied to cities that require a
balanced network supply with limited resources.
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dc.description.tableofcontentsChapter 1. Introduction ···········································1
1.1 Background ·····································································1
1.2 Research Scope ·····························································4
Chapter 2. Literature Review ·······························7
2.1 Transit Network Design ···········································7
2.2 Unmet Demand ······························································12
2.3 Equity ················································································17
2.4 Algorithm ·········································································26
2.4.1 Multi-objective Optimization ········································26
2.4.2 Local Search ·····································································31
2.5 Summary and Research Direction ·································34
Chapter 3. Methodology ··········································37
3.1 NSGA-II ···········································································37
3.2 Algorithm ·········································································40
3.2.1 Procedure and Network Encoding ······························40
3.2.2 Cross-over and Mutation ··············································43
3.2.3 Local search ······································································44
Chapter 4. Model Formulation ·····························47
4.1 Summary ··········································································47
4.2 Assumption and Variables ·······································48
4.3 Model Formulation ·······················································52
4.3.1 Objective Function ··························································52
4.3.2 Logit Model ······································································54
4.3.3 Traffic Assignment ·························································56
4.3.4 Transit Assignment ······················································58
Chapter 5. Numerical Example ····························61
5.1 Toy Network ································································61
5.1.1 Network Explanation ····················································61
5.1.2 Result Analysis ································································65
5.1.3 Marginal Effect ································································75
5.1.4 Comparison with Previous Research ·························80
5.2 Large Network ······························································83
5.2.1 Network Explanation ······················································83
5.2.2 Result Analysis ································································86
5.2.3 Marginal Effect ································································91
5.2.4 Comparison with Previous Study ·······························92
5.3 Discussion ·······································································94
Chapter 6. Result and Future Research ·········· 97
Reference ·······································································100
Appendix ·······································································110
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dc.language.isoeng-
dc.publisher서울대학교 대학원-
dc.subjectTNDFSP-
dc.subjectEquity-
dc.subjectUnmet Demand-
dc.subjectMulti-Objective-
dc.subjectPareto Optimal-
dc.subject.ddc624-
dc.titleMulti-objective Optimization for Bus Network Design Problem Using Pareto Optimal-
dc.title.alternative파레토최적해를 이용한 버스네트워크 설계 다목적 최적화-
dc.typeThesis-
dc.typeDissertation-
dc.contributor.department공과대학 건설환경공학부-
dc.description.degreeDoctor-
dc.date.awarded2020-08-
dc.identifier.uciI804:11032-000000163243-
dc.identifier.holdings000000000043▲000000000048▲000000163243▲-
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