Vehicle Scheduling for Public Mass Transit — An Overview

Daduna, Joachim R.; Paixão, José M. P.

doi:10.1007/978-3-642-57762-8_6

Cited by 60 publications

(27 citation statements)

References 21 publications

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“…Overviews of algorithms and applications for the singledepot VSP (SDVSP) and some of its extensions can be found in [1,5,10,12,18]. The SDVSP has been formulated as a linear assignment problem, a transportation problem, a minimum-cost flow problem, a quasi-assignment problem, and a matching problem in the literature.…”

Section: Literature Reviewmentioning

confidence: 99%

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The vehicle rescheduling problem: Model and algorithms

Mirchandani

Borenstein

2007

Networks

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When a vehicle on a scheduled trip breaks down, one or more vehicles need to be rescheduled to serve the customers on that trip with minimum operating and delay costs. The problem of reassigning vehicles in real-time to this cut trip as well as to other scheduled trips with given starting and ending times, is referred to as the vehicle rescheduling problem (VRSP). This paper considers modeling, algorithmic, and computational aspects of the single-depot VRSP. The paper formulates a model for this problem and develops several fast algorithms to solve it, including parallel synchronous auction algorithms. The concept of the common feasible network (CFN) is introduced to find a good set of initial "prices" for speeding up the auction algorithm. Computational experiments on randomly generated problems are described. Computational results show that, for small problems, all of the developed algorithms demonstrate very good computational performances. For large problems, parallel CFN-based auction algorithms provide the optimal solution with much smaller computation times.

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Section: Literature Reviewmentioning

confidence: 99%

“…The literature describes several different approaches to solve the VSP [12], but the literature on VRSP is scant. However, when fleet size is limited and disruptions are frequent, good automated rescheduling tools to assist decision makers become important.…”

Section: Introductionmentioning

confidence: 99%

The vehicle rescheduling problem: Model and algorithms

Mirchandani

Borenstein

2007

Networks

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“…Vehicle scheduling and crew scheduling have been a subject of numerous research activities, due to the significant gains that may result from their optimization (Daduna and Paixão, 1995;Wren and Rousseau, 1999).…”

Section: Introductionmentioning

confidence: 99%

A multiobjective metaheuristic approach for the integrated vehicle and crew scheduling

Prata

2016

J. Transp. Lit.

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Article Info AbstractKeywords: mass transit combinatorial optimization evolutionary algorithmsThe integrated vehicle and crew scheduling problem is a hard Combinatorial Optimization problem widely studied over the years. Taking into consideration the range of variables related to the planning process of vehicles and drivers, there are several practical characteristics of the problem that are not reflected in the solutions generated computationally. Among these characteristics, that were not found in the consulted literature, the most important is the existence of multiple objectives. This paper aims at presenting a multiobjective approach for the integrated vehicle and crew scheduling problem based on Genetic Algorithms. A case study in Portimão (Portugal) is presented and discussed. IntroductionIn what concerns buses, urban transportation planning can be divided in several steps, often considered as follows: network design, timetable creation, vehicle scheduling, crew scheduling and crew rostering. Vehicle scheduling and crew scheduling have been a subject of numerous research activities, due to the significant gains that may result from their optimization (Daduna and Paixão, 1995; Wren and Rousseau, 1999).Several researchers have reported the strong interaction between the vehicle scheduling problem and the crew scheduling problem, emphasizing the gains that can be obtained by considering them together (Freling et al., 2003). The integrated problem is usually known as the Vehicle and Crew Scheduling Problem (VCSP).Traditionally, vehicle scheduling and crew scheduling are done separately and in a sequential manner. The Vehicle Scheduling Problem (VSP) is performed in a first stage, being followed by the Crew Scheduling Problem (CSP). Usually, the CSP is more complex than the VSP, and therefore, in general, it is not a suitable strategy to schedule the vehicles without taking into account the requirements for the crews, since these may form the bottleneck of the whole process.In many public transport companies, particularly in developing countries, the costs of crews and drivers are the most significant. Thus, efforts should be focused in minimizing such costs, even when vehicle scheduling is being performed.For the resolution of the VCSP, several approaches have been reported in the literature. Exact optimization methods, based on branch-and-bound, branch-and-cut, column generation, or lagrangian relaxation are presented by Friberg and Haase (1999), Gaffi and Nonato (1999) Approaches based on heuristics and metaheuristics are presented in Ball et al. (1983), Falkner andRyan (1992), Patrikalakis and Xerocostas (1992), Wren and Gualda (1999), Valouxis and Housos (2002), Rodrigues et al. (2006), Laurent and Hao (2007), Steinzen et al. (2007 and Bartodziej et al. (2009). However, the reported heuristic techniques are not easy to generalize and most of them have been developed for very specific problems, with results reported for a small number of instances.Taking into consideration the range of variables related t...

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“…Approaches include decomposition models (Saha 1972), assignment models (Orloff 1976), transportation models (Gavish and Shlifer 1978) or network flow models (Daduna and Paixao 1995). A recent survey paper dealing with bus scheduling is Bunte and Kliewer (2009), railway issues are treated in Maróti (2006).…”

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confidence: 99%

Integrating line planning, timetabling, and vehicle scheduling: a customer-oriented heuristic

Michaelis

Schöbel

2009

Public Transp

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Given an existing public transportation network, the classic planning process in public transportation is as follows: In a first step, the lines are designed; in a second step a timetable is calculated and finally the vehicle and crew schedules are planned. The drawback of this sequence is that the main factors for the costs (i.e. the number of vehicles and drivers needed) are only determined in a late stage of the planning process.We hence suggest to reorder the classic sequence of the planning steps: In our new approach we first design the vehicle routes, then split them to lines and finally calculate a (periodic) timetable. The advantage is that costs can be controlled during the whole process while the objective in all three steps is customer-oriented.In the paper we formulate an integrated model from which we develop this new approach, discuss the complexity of the resulting problems, and present a heuristic which we applied within a case study, optimizing the local bus system in Göttingen, Germany. Motivation and related literatureAccording to Desaulniers and Hickman (2007) the planning process in public transportation includes several phases such as strategic planning (e.g. network design), tactical planning (as line planning or timetabling), operational planning (e.g. vehicle scheduling) and real time control. The usual sequence of these planning steps is sketched in Fig. 1, see e.g. Ceder and Wilson (1986), Liebchen and Möhring (2007).

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Vehicle Scheduling for Public Mass Transit — An Overview

Cited by 60 publications

References 21 publications

The vehicle rescheduling problem: Model and algorithms

The vehicle rescheduling problem: Model and algorithms

A multiobjective metaheuristic approach for the integrated vehicle and crew scheduling

Integrating line planning, timetabling, and vehicle scheduling: a customer-oriented heuristic

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