01478229

Component

https://doi.org/10.3141/2399-03

http://scholar.google.com...heng&publication_year=2013

The transportation network design problem (NDP) is a high capital investment decision-making problem that inherently involves both subjective and objective uncertainties as well as multiple objectives. Goal programming is a practically useful approach with an explicit consideration of planners’ goal setting and priority structure among the multiple objectives. This paper describes the development of a hybrid goal programming (HGP) approach for modeling both subjective and objective uncertainties simultaneously in the NDP decision-making process. Planners’ subjective uncertainty regarding the linguistic setting of goals and priority structure is characterized as a set of fuzzy variables with nonlinear achievement and satisfaction functions, and the objective travel demand uncertainty is characterized as a set of random variables with predefined probability distributions. The HGP-NDP is formulated as a chance-constrained model in a bi-level programming framework and solved by a genetic algorithm procedure based on random simulation and fuzzy evaluation. The paper provides numerical examples and a real case study to demonstrate the features and applicability of the proposed HGP approach in solving the NDP under an uncertain environment.

01517323

13-2770

English

pp 23–33

2013

Transportation Research Record: Journal of the Transportation Research Board

9780309294843

Print

Figures (5) ; Maps; References (28) ; Tables (3)

Decision making; Fuzzy sets; Genetic algorithms; Simulation; Strategic planning; Transportation planning; Uncertainty

Network design problem

Administration and Management; Planning and Forecasting; Transportation (General); I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Feb 5 2013 12:34PM

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