Modeling Park-and-Ride Services in a Multimodal Transport Network with Elastic Demand

Li, Zhichun; Lam, William H. K.; Wong, S. C.; Dao-li, Zhu; Huang, Hai

doi:10.3141/1994-14

Cited by 68 publications

(49 citation statements)

References 15 publications

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“…The positive sides of Park & Ride system are noticed also by Li et al, [15] claiming that P&R schemes have been widely recognized as an effective means of addressing traffic congestion problems in densely developed urban areas. These schemes are used as a tool to encourage commuters to undertake their journeys in two parts: first driving a private car to a car park near transit stations and then completing the remainder of the journey by taking a transit mode.…”

Section: Park and Ridementioning

confidence: 81%

An Attitude of Subcarpathian’s Residents to Sustainable Solutions for Urban Transport

Zimon

2016

ILNS

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ABSTRACT. Sustainable development is a concept that appears more frequently in the context of urbanized cities. Rational management of city logistics and urban population change of consciousness becomes a priority. The purpose of this publication is to emphasize the need for changes in city logistics, to characterize the concept of sustainable transport and to present the results of research on: the views of residents of Podkarpacie on choosing alternatives to the car, and urban transport concept. The research process was conducted in two stages. The first stage of the research was conducted in 2014 within its scope included the study compared the inhabitants of Podkarpacie to sustainable forms of transport. The second stage of the study carried out in 2015 was designed to examine whether the implementation of Intelligent Public Transport Management System, has changed the ratio of respondents to sustainable transport.

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Section: Park and Ridementioning

confidence: 81%

An Attitude of Subcarpathian’s Residents to Sustainable Solutions for Urban Transport

Zimon

2016

ILNS

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“…Concerning the existence and uniqueness of the VI Eq. (A.1) solution, relevant discussions are the same with those about the fixed point, so omitted here (Fisk, Boyce 1983;Li et al 2007b). Nagurney (2010a) showed that VI problems have unique solutions when some monotonic conditions are satisfied.…”

Section: Appendixmentioning

confidence: 99%

Optimal location and size of logistics parks in a regional logistics network with economies of scale and CO2 emission taxes

Zhang

Eglese

2015

Transport

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Abstract. This paper proposes a model to address the design problem of a regional logistics network. In the proposed model, the decision variables include the location and size of logistics parks. The interaction between the logistics authority and logistics users as well as the effects of economies of scale and CO 2 emission taxes on the logistics network design are explicitly considered. The proposed model is formulated as a bi-level formulation, in which the upper level aims to maximize total social welfare of the system by determining the optimal location and size of logistics parks with CO 2 emission taxes consideration, whereas the lower level describes the logistics users' choices for service routes. A heuristic solution algorithm is presented to solve the proposed model, and a numerical example is given to illustrate the applications of the proposed model and solution algorithm. The findings show that the optimal location and size of logistics parks depend on the realized logistics demand and the level of the economies of scale. The CO 2 emission taxation can help to improve the total social welfare of the system and drive the logistics users to choose greener transportation modes.

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“…Concerning the existence and uniqueness of the VI equation solution, relevant discussions are the same with those about the fixed point, so omitted here. 61,62 Charnes et al 63 showed that VI problems have unique solutions when some monotonic conditions are satisfied.…”

Section: Conclusion and Further Studiesmentioning

confidence: 99%

A robust optimization model for green regional logistics network design with uncertainty in future logistics demand

Zhang

Huang

et al. 2015

Advances in Mechanical Engineering

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This article proposes a new model to address the design problem of a sustainable regional logistics network with uncertainty in future logistics demand. In the proposed model, the future logistics demand is assumed to be a random variable with a given probability distribution. A set of chance constraints with regard to logistics service capacity and environmental impacts is incorporated to consider the sustainability of logistics network design. The proposed model is formulated as a two-stage robust optimization problem. The first-stage problem before the realization of future logistics demand aims to minimize a risk-averse objective by determining the optimal location and size of logistics parks with CO 2 emission taxes consideration. The second stage after the uncertain logistics demand has been determined is a scenario-based stochastic logistics service route choices equilibrium problem. A heuristic solution algorithm, which is a combination of penalty function method, genetic algorithm, and Gauss-Seidel decomposition approach, is developed to solve the proposed model. An illustrative example is given to show the application of the proposed model and solution algorithm. The findings show that total social welfare of the logistics system depends very much on the level of uncertainty in future logistics demand, capital budget for logistics parks, and confidence levels of the chance constraints.

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Modeling Park-and-Ride Services in a Multimodal Transport Network with Elastic Demand

Cited by 68 publications

References 15 publications

An Attitude of Subcarpathian’s Residents to Sustainable Solutions for Urban Transport

An Attitude of Subcarpathian’s Residents to Sustainable Solutions for Urban Transport

Optimal location and size of logistics parks in a regional logistics network with economies of scale and CO2 emission taxes

A robust optimization model for green regional logistics network design with uncertainty in future logistics demand

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