A computerized approach to the New York City school bus routing problem

Braca, Jeffrey; Bramel, Julien; POSNER, BRUCE; Simchi‐Levi, David

doi:10.1080/07408179708966379

Cited by 108 publications

(88 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We started with the "Manhattan Project," an implementation and validation of the heuristic with data only from Manhattan. The algorithm showed great promise-it used substantially fewer buses than what the city used; see Braca et al (1997). These results motivated the city, with our help, to integrate the algorithm as part of a decision support system that included a large database, a module for visualization of pick-up points, routes displayed on a geographic information system, and our optimization engine.…”

Section: From Theory To Practicementioning

confidence: 93%

OM Forum—OM Research: From Problem-Driven to Data-Driven Research

Simchi‐Levi

2014

M&SOM

Self Cite

View full text Add to dashboard Cite

show abstract

Section: From Theory To Practicementioning

confidence: 93%

OM Forum—OM Research: From Problem-Driven to Data-Driven Research

Simchi‐Levi

2014

M&SOM

Self Cite

View full text Add to dashboard Cite

show abstract

“…Ripplinger (2005) focused on rural school vehicle routing and pro vides models and analysis for separating special needs student transportation from general students and generating single routes for both types of students. Braca et al (1997) briefly mentions special needs students in one part of their research. The authors describe the difference between special needs students and general stu dents, but did not develop any pertinent or applicable transportation models for the research problem under study.…”

Section: Previous Researchmentioning

confidence: 99%

An Analysis of Special Needs Student Busing

Kamali¹,

Mason²,

Pohl³

2013

JPT

View full text Add to dashboard Cite

Population growth can lead to public school capacity issues as well as increased school bus utilization, which, in turn, can result in longer school bus transport times for regular and special needs students. Special needs or medically fragile students are children with special health care needs who are at increased health and safety risk. It is common practice to provide special needs students with specially-equipped buses and/or special classroom environments with specific facilities or services. However, the assignment of student services to schools is regularly made without regard to bus transportation considerations for special needs students. Considering the potentially negative impact of long school bus rides on these students, we present the first sys tematic, integrated analyses of special needs student busing and classroom assign ments. We provide models and algorithms for maintaining administration-based transportation financial performance measures while simultaneously designing smarter transportation networks considering both student geographical location and service needs.

show abstract

“…In this way, VRPTW is able to improve service quality. VRPTW has a wide range of applications, such as distribution requirements planning [1,2], material handling systems [3], bank deliveries [4], postal deliveries [5], school bus routing [6] and so on. Actually, VRPTW has been a research field of great interest, and many different solving algorithms have been proposed.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Chaos-Particle Swarm Optimization Algorithm for the Vehicle Routing Problem with Time Window

Liang

Peng

et al. 2013

Entropy

View full text Add to dashboard Cite

State-of-the-art heuristic algorithms to solve the vehicle routing problem with time windows (VRPTW) usually present slow speeds during the early iterations and easily fall into local optimal solutions. Focusing on solving the above problems, this paper analyzes the particle encoding and decoding strategy of the particle swarm optimization algorithm, the construction of the vehicle route and the judgment of the local optimal solution. Based on these, a hybrid chaos-particle swarm optimization algorithm (HPSO) is proposed to solve VRPTW. The chaos algorithm is employed to re-initialize the particle swarm. An efficient insertion heuristic algorithm is also proposed to build the valid vehicle route in the particle decoding process. A particle swarm premature convergence judgment mechanism is formulated and combined with the chaos algorithm and Gaussian mutation into HPSO when the particle swarm falls into the local convergence. Extensive experiments are carried out to test the parameter settings in the insertion heuristic algorithm and to evaluate that they are corresponding to the data's real-distribution in the concrete problem. It is also revealed that the HPSO achieves a better performance than the other state-of-the-art algorithms on solving VRPTW.

show abstract

A computerized approach to the New York City school bus routing problem

Cited by 108 publications

References 10 publications

OM Forum—OM Research: From Problem-Driven to Data-Driven Research

OM Forum—OM Research: From Problem-Driven to Data-Driven Research

An Analysis of Special Needs Student Busing

A Hybrid Chaos-Particle Swarm Optimization Algorithm for the Vehicle Routing Problem with Time Window

Contact Info

Product

Resources

About