Aggregation in Network Models for Transportation Planning

Cullen, Daniel; Kuhn, Harold; Frank, Marguerite

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Aggregation in Network Models for Transportation Planning

1978-02-01
By Cullen, Daniel ; Kuhn, Harold ; Frank, Marguerite

File Language:

English

Details

Creators:

Cullen, Daniel ; Kuhn, Harold ; Frank, Marguerite
Corporate Creators:

Mathematica Policy Research, Inc.
Corporate Contributors:

John A. Volpe National Transportation Systems Center, (U.S.)
Subject/TRT Terms:
Publication/ Report Number:

DOT-TSC-RSPD-78-7
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

United States. Dept. of Transportation. Research and Special Programs Directorate
NTL Classification:

NTL-PLANNING AND POLICY-PLANNING AND POLICY ; NTL-ECONOMICS AND FINANCE-ECONOMICS AND FINANCE ; NTL-ECONOMICS AND FINANCE-Economic Impacts
Description:

This report documents research performed on techniques of aggregation applied to network models used in transportation planning. The central objective of this research has been to identify, extend, and evaluate methods of aggregation so as to improve the capabilities of the transportation planner by better computational methods, by more flexible models, and by increased confidence in the results obtained from aggregated models. The results of the research are presented in a series of papers. Papers 1 and 2 address the question of error bounding in the lifted (disaggregated) solution using the application of duality theory. Paper 3 reviews the potential performance of a new algorithm for the equilibrium model using path extraction aggregation. Paper 4 addresses potential savings of aggregation. Paper 5 presents results on aggregation test networks and attempts to formulate rules for equilibrium models. Papers 6 and 7 present specific mathematical results on two aggregation-related problems.
Format:

PDF
Funding:

DOT-TSC-883
Download URL:

https://rosap.ntl.bts.gov/view/dot/10491/dot_10491_DS1.pdf
File Type:

[PDF - 4.23 MB]
Collection(s):

Volpe Center
Main Document Checksum:

urn:sha256:aa49a29f9d2eeaba46f12fc7361bad6dc9f1266764f909dde692708d070dd02b

File Language:

English

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