On some matching problems arising in vehicle scheduling models

Bertossi, Alan A.; Carraresi, Paolo; Gallo, Giorgio

doi:10.1002/net.3230170303

Cited by 199 publications

(82 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The multi-depot vehicle scheduling problem (MDVSP) was proved to be NP-hard even for two depots (see Bertossi et al (1987)). Some exact algorithms, presented by Fischetti et al (1989), Forbes et al (1994) and Kliewer et al (2006), were able to solve instances with up to thousands of trips.…”

Section: Literature Reviewmentioning

confidence: 99%

A GRASP with efficient neighborhood search for the integrated maintenance and bus scheduling problem

Hama

Yagiura

2018

JAMDSM

View full text Add to dashboard Cite

The overall planning process undertaken by a bus company is traditionally composed of five sub-processes: timetabling, vehicle scheduling, maintenance scheduling, crew scheduling, and crew rostering. Solving the full optimization problem is believed to be computationally intractable, and therefore in practice the five sub-processes are usually optimized in sequence. In this paper, we present a model that integrates the problems of vehicle scheduling and maintenance scheduling. The objective is to minimize the differences in mileage between buses, the total distance traveled, and the daily differences in the number of maintenance tasks. We propose a heuristic algorithm using the framework of greedy randomized adaptive search procedure (GRASP), and we improve the neighborhood search procedure by using an ordered list of possible trips. We compare the neighborhood search procedure with and without this mechanism and show that the ordered list reduces the number of neighbors to be checked by more than 95%, and it reduces the time to obtain solutions of the same or better quality by an average of 70%. Through computational experiments on instances generated from real-world data, we show that the proposed algorithm finds solutions that are as good as or better than those obtained by a commercial solver in less than 5% of the time required by the latter.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A GRASP with efficient neighborhood search for the integrated maintenance and bus scheduling problem

Hama

Yagiura

2018

JAMDSM

View full text Add to dashboard Cite

show abstract

“…The MDVSP is shown to be NP-hard by Bertossi et al (1987), which is in strong contrast with the polynomial solvability of the SDVSP, see e.g., Freling et al (2001). An overview of different vehicle scheduling models can be found in (Bunte and Kliewer, 2009).…”

Section: Sequential Vehicle and Crew Schedulingmentioning

confidence: 99%

Computing strong lower and upper bounds for the integrated multiple-depot vehicle and crew scheduling problem with branch-and-price

Horváth

Kis

2017

Cent Eur J Oper Res

View full text Add to dashboard Cite

In the problem of the title, vehicle and crew schedules are to be determined simultaneously in order to satisfy a given set of trips over time. The vehicles and the crew are assigned to depots, and a number of rules have to be observed in the course of constructing feasible schedules. The main contribution of the paper is a novel mathematical programming formulation which combines ideas from known models, and an exact solution procedure based on branch-and-price.The method is tested on benchmark instances from the literature and it provides suboptimal schedules using limited computational resources.Keywords vehicle and crew scheduling · branch-and-price · exact methods · integer programming

show abstract

“…The networks overlay by vehicle type enables a service trip can be in multiple layers, and hence these layers cannot be solved independently, featuring the VTSP as a multicommodity flow problem. Consequently, the problem becomes NP-hard [16]- [18] …”

Section: Figure 1 Example Of Tsnmentioning

confidence: 99%

Towards Integrating Retiming in Vehicle Type Scheduling Problem

Sigua

Campoverde²,

Borenstein

2017

REP

View full text Add to dashboard Cite

ResumenEn este documento, proponemos una programación lineal entera (ILP) con el objetivo de optimizar la generación de horarios y el problema de programación de tipo de vehículo (VTSP), basado en una red de tiempo y espacio (TSN). El modelo se definió como un problema de programación de tipo de vehículo con cambios secuenciales de horario (VTSP-SCT). Además, desarrollamos una nueva metodología para insertar una ventana de tiempo al problema propuesto en base a pequeños cambios en la estructura TSN, con una implementación computacional sencilla y una solución óptima en tiempos de ejecución de computación bajos. Al incluir pequeños cambios en el cronograma y/o incluir ventanas de tiempo para programar viajes, introdujimos niveles de flexibilidad en los horarios de salida de los viajes, lo que resulta en ventajas operacionales para el proveedor del servicio. Dado que usamos un intervalo de ventana de tiempo muy corto, el horario actual solo se modifica ligeramente, cambiando mínimamente las rutinas de los pasajeros. Los enfoques desarrollados fueron probados usando instancias aleatorias basadas en una ciudad brasileña. El VTSP-SCT con y sin ventanas de tiempo ha resultado en ahorros relevantes en las operaciones diarias del servicio de transporte público, reduciendo el número requerido de vehículos programados para llevar a cabo la demanda histórica. Palabras clave: programación de vehículos, logística, transporte público, investigación de operaciones, programación de horarios AbstractIn this paper, we propose an integer linear programming (ILP) aiming at optimizing timetabling generation and the Vehicle Type Scheduling Problem (VTSP), based on a time-space network (TSN). The model was defined as Vehicle Type Scheduling Problem with Sequential Changes of timetable (VTSP-SCT). Additionally, we developed a new methodology to insert time window to the proposed problem based on small changes on the TSN structure, with easy computational implementation and optimal solution at low computation run-times. By including small changes to the timetable and/or including time windows for timetabling trips, we introduced flexibility levels in the departure times of trips, resulting in operational advantages for the service provider. Since we use a very short time window interval, the current timetable is only slightly modified, minimally changing the passenger routines. The developed approaches were tested using random instances based on a Brazilian city. The VTSP-SCT with and without time windows have resulted in relevant savings in the daily operations of the public transportation service, reducing the required number of scheduled vehicles to carry out the historic demand.

show abstract

On some matching problems arising in vehicle scheduling models

Cited by 199 publications

References 6 publications

A GRASP with efficient neighborhood search for the integrated maintenance and bus scheduling problem

A GRASP with efficient neighborhood search for the integrated maintenance and bus scheduling problem

Computing strong lower and upper bounds for the integrated multiple-depot vehicle and crew scheduling problem with branch-and-price

Towards Integrating Retiming in Vehicle Type Scheduling Problem

Contact Info

Product

Resources

About