p-Hub approach for the optimal park-and-ride facility location problem | Semantic Scholar (2024)

A rounding heuristic is developed that identifies extremely fast a decent solution to a realistic scale of the nonlinear P&R facility location problem and a genetic algorithm is developed to compare its performance with that of the adaptive randomized rounding algorithm.

This work generalizes the MNL model to a nested logit (NL) model and develops two computational methods—neighborhood search and randomized rounding—to solve large-scale P&R facility location problems under the NL demand function.

A recently developed Weibit-based model was adopted to represent the traveler choice behavior with heterogeneity and the model’s independence of irrelevant alternatives property was explored and used to linearize its nonlinear probability.

The greedy and the tabu search algorithms were chosen and implemented and the optimal locations for P&R were determined, and the DS composed of 3 hubs was obtained, in contrast to the existing 14 elements.

A bi-level model for determination of optimal location and capacity of a remote P&R (RPR) facility that allows a user to park a vehicle in a suburban area at lower cost and then take a bus to the nearby train station, thus improving the social benefit dramatically.

A multi-objective bi-level model that jointly optimizes the P&R facility locations and the ATR scheme (the ATR areas and the proportion of restricted private cars) and minimizes the total travel cost and total emission cost and maximizes consumer surplus is proposed.

The study provides a heretofore missing theoretical framework for integrated planning of P&R facilities and transit services and demonstrates that the optimal design shifts commuters from the automobile mode to transit and P &R modes and, hence, improves the net social benefit dramatically.

A bi-objective programming model (BP) with spatial equity constraints is proposed to site park-and-ride (P&R) facilities in traffic networks and application results show the trade-offs associated with passenger flow volume, cost and passenger flowvolume per cost.

A non-parametric approach is used in this paper to test three key aspects of the P&R facility localisation process, and shows that the AHP method is a powerful technique for evaluating and comparing the influence of multiple factors on each other and on the final outcome.

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This paper presents a new quadratic integer formulation for the Uncapacitated Hub Location Problem (UHP), which is based on the idea of multi-commodity flows in networks, and lends itself well for using a branch-and-bound procedure to find optimal solutions.

This work proposes a model for locating multi-server facilities in such a way as to maximize market capture by the entering firm, when customers choose the facilities they patronize, by the travel time to the facility and the waiting time at the facility.

A p-hub median is defined, analogous to a p-median, and integer programming formulations for the multiple and single allocation p-Hub median problems are presented, and two new heuristics for the single allocations p- hub median problem are evaluated.

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