Heterogeneous Parking Market Subject to Parking Rationing

Bagloee, Saeed Asadi; Asadi, Mohsen

doi:10.1155/2015/847324

Cited by 3 publications

(2 citation statements)

References 37 publications

(54 reference statements)

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“…The methodology proposed in this work could be further improved by expanding the traffic assignment to multi-class and multi-modal traffic flow. To enhance realism and fidelity of the traffic assignment models, the idea of subjecting the DNDP to a parking search model [ 62 , 63 ] as well as dynamic network design assignment is of highest practical relevance that paves the way to use some off-the-shelf simulation software (the computational expense is, however, a serious concern [ 6 , 64 , 65 ]). In light of the scarcity of resources and cash flow issues, prioritization of selected projects out of solving the DNDP is also a demanding problem in the industry which deserves to be addressed [ 66 ].…”

Section: Discussionmentioning

confidence: 99%

An outer approximation method for the road network design problem

Bagloee

Sarvi

2018

PLoS ONE

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Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well.

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Section: Discussionmentioning

confidence: 99%

An outer approximation method for the road network design problem

Bagloee

Sarvi

2018

PLoS ONE

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“…In the demand side, congestion pricing, originally proposed in the economic literature [10], has emerged as a significant leverage to bring balance back to the supply-demand equation. Economists, who believe in the power of a free market, seek solutions in the cost and pricing mechanism when they see any supply-demand imbalance [11,12].…”

Section: Introductionmentioning

confidence: 99%

A modern congestion pricing policy for urban traffic: subsidy plus toll

Bagloee

Sarvi

2017

J. Mod. Transport.

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Congestion pricing is seen as an effective policy to address traffic congestion. In such policies where money, people and authorities are involved, the success generally hinges upon two factors: equity (being fair) and acceptability (to both people and authorities). The primary concern is the equity, for which ''tradable credit scheme (TCS)'' has been introduced and extensively studied in the literature. Nevertheless, due to the complexity of the trading schemes, the TCS has yet to find any foot in the real world. To this end, a novel idea of rewarding has substituted the trading component to be known as toll-and-subsidy scheme (TSS). The idea is to charge the drivers on some roads (toll) while rewarding them to use other alternative-and perhaps underutilizedroads (subsidy). The research of the TSS is in its infancy stage. The problem to be tackled in this study is as follows: Given a set of roads constituting a cordon line around the central business district (CBD) or across a screen line, how much toll or subsidy should be assigned to each road? The problem is first transformed into a capacitated traffic assignment problem. We employ a solution method based on augmenting the travel time of roads up to the level at which the traffic volumes do not exceed some target rates. A real dataset from the city of Winnipeg, Canada, is used as a pilot study. We then discuss policy-related applications of the TSS. It is proved in the literature that one can obtain optimal TSSs for various objectives and considerations. To this end, the non-negativity of the toll values is relaxed which results in a valid toll set. Nevertheless, the computational time is found to be of highest significance. Our method differs in the fact that the traffic volumes are bounded from the above and it is quite affordable. The main contribution is first to highlight the concept of subsidy along with traditional thought of merely toll. Second is to interpret the Lagrangian values of the capacity constraints as the values of the toll/subsidy.

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Improving Drilling Rate of Penetration Modelling Performance Using Adaptive Neuro-Fuzzy Inference Systems

Hamdi¹,

Haldavnekar²,

Momeni

et al. 2020

Day 1 Mon, November 09, 2020

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Rate of penetration (ROP) modeling is one of the most important objectives of any drilling program. Penetration model depends on different criteria such as mud weight (MW), weight on bit (WOB), rotary speed (N), and so forth. It is a complex process, because of the high number of variables and uncertainties. Different mathematical models and evaluation methods were developed to solve this problem but they were unable to attain desirable accuracy. Adaptive neuro-fuzzy inference systems (ANFIS) could be used in these cases to predict the rate of penetration. ANFIS is a combination of neural networks and fuzzy logic networks and could be used to create a robust ROP model. The objective of this study is to apply the ANFIS method and compare the modeling results with conventional artificial neural network models. ANFIS trains the model using a set amount of data and then validates it against random data to measure the error. Drill bit record from a certain field has been taken as training data and testing data for the program. The selection process uses the Sugeno model for generating the fuzzy model and the backpropagation and gradient descent method for recognizing the patterns. The data was normalized and sorted out to remove the incomplete values. Tests were done by applying 2 and 3 membership functions to a 4 input interface and a 5 input interface. The accuracy of the results depends on the numbers of inputs and membership functions. Each input was tested with different membership functions to test the data. The output generated from the training process showed that sigmoid function and Gaussian function with grid partitioning and linear output function yielded the best results for 4 and 5 inputs using 2 and 3 membership functions each. The training error recorded was about 3 percent with a checking error of 20 percent for most cases.

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Heterogeneous Parking Market Subject to Parking Rationing

Cited by 3 publications

References 37 publications

An outer approximation method for the road network design problem

An outer approximation method for the road network design problem

A modern congestion pricing policy for urban traffic: subsidy plus toll

Improving Drilling Rate of Penetration Modelling Performance Using Adaptive Neuro-Fuzzy Inference Systems

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