Journal ArticleDOI
Optimizing bus stop spacing in urban areas
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TLDR
In this paper, a bi-level optimization model for locating bus stops to minimize the social cost of the overall transport system is developed, taking into account possible changes in demand due to different bus stop locations considering congestion on buses, interaction with private traffic, operational variables (fleet, frequency, operator budgets), and the socio-demographic characteristics of each zone in the urban area.Abstract:
This work develops a bi-level optimization model for locating bus stops to minimize the social cost of the overall transport system. The work takes into account possible changes in demand due to different bus stop locations considering congestion on buses, interaction with private traffic, operational variables (fleet, frequency, operator budgets), and the socio-demographic characteristics of each zone in the urban area. Finally, the technique is applied to a real case and a sensitivity analysis is performed to check how the different variables analysed influence the solution provided by the model.read more
Citations
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Journal ArticleDOI
Design of limited-stop bus service with capacity constraint and stochastic travel time
TL;DR: A hybrid artificial bee colony (ABC) and Monte Carlo method is developed to solve the optimal stopping strategy of limited-stop bus service, which allows each bus vehicle to skip some stops.
Journal ArticleDOI
Estimation of travel time and the benefits of upgrading the fare payment technology in urban bus services
TL;DR: A comparative assessment of speed gains with two policies aimed at reducing bus travel times – providing dedicated busways and upgrading the fare collection system – shows that the number of passengers is crucial in determining the advantage of one or the other in increasing bus operating speed.
Journal ArticleDOI
The economics and engineering of bus stops: Spacing, design and congestion
TL;DR: It is found that bus stop spacing should be decreased if demand increases at a constant busRunning speed; however, if both bus running speed and the speed of the passenger boarding process increase, then the distance between bus stops should be kept long even at high demand levels, a result that is consistent with the implementation of Bus Rapid Transit systems that feature high bus running speeds and long distances between stops.
Journal ArticleDOI
A comprehensive evacuation planning model and genetic solution algorithm
TL;DR: A macroscopic multi-criteria optimization model is proposed that includes several such questions simultaneously simultaneously, and a genetic algorithm is developed to solve the problem heuristically.
Journal ArticleDOI
Complete hierarchical multi-objective genetic algorithm for transit network design problem
Mahmoud Owais,Mostafa K. Osman +1 more
TL;DR: Genetic Algorithm (GA) is presented as a complete constructive multi-objective algorithm that creates its own routes from scratch then assembles the routes into efficient transit networks to produce the optimal (near optimal) Pareto front solutions.
References
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Journal ArticleDOI
`` Direct Search'' Solution of Numerical and Statistical Problems
Robert Hooke,T. A. Jeeves +1 more
TL;DR: The phrase "direct search" is used to describe sequential examination of trial solutions involving comparison of each trial solution with the "best" obtained up to that time together with a strategy for determining (as a function of earlier results) what the next trial solution will be.
Journal ArticleDOI
Bus network design
Avishai Ceder,Nigel H. M. Wilson +1 more
TL;DR: In this article, an algorithm is presented that can be used to design new bus routes taking account of both passenger and operator interests; however, this algorithm focuses on only a single component of the overall bus operations planning process described in this paper.
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