The crew-scheduling module in the GIST system

The public transportation is gaining importance every year basically due the population growth, environmental policies and, route and street congestion. Too able an efficient management of all the resources related to public transportation, several techniques from different areas are being applied and several projects in Transportation Planning Systems, in different countries, are being developed. In this work, we present the GIST Planning Transportation Systems, a Portuguese project involving two universities and six public transportation companies. We describe in detail one of the most relevant modules of this project, the crew-scheduling module. The crew-scheduling module is based on the application of meta-heuristics, in particular GRASP, tabu search and genetic algorithm to solve the bus-driver-scheduling problem. The metaheuristics have been successfully incorporated in the GIST Planning Transportation Systems and are actually used by several companies.Integrated transportation systems, crew scheduling, metaheuristics

A solution approach for dynamic vehicle and crew scheduling

In this paper, we discuss the dynamic vehicle and crew schedulingproblem and we propose a solution approach consisting of solving asequence of optimization problems. Furthermore, we explain why itis useful to consider such a dynamic approach and compare it witha static one. Moreover, we perform a sensitivity analysis on ourmain assumption that the travel times of the trips are knownexactly a certain amount of time before actual operation.We provide extensive computational results on some real-world datainstances of a large public transport company in the Netherlands.Due to the complexity of the vehicle and crew scheduling problem,we solve only small and medium-sized instances with such a dynamicapproach. We show that the results are good in the case of asingle depot. However, in the multiple-depot case, the dynamicapproach does not perform so well. We investigate why this is thecase and conclude that the fact that the instance has to be splitin several smaller ones, has a negative effect on the performance.transportation;vehicle and crew scheduling;large-scale optimization;dynamic planning

Multiple-Depot Integrated Vehicle and Crew Scheduling

This paper presents two different models and algorithms for integrated vehicle and crew scheduling in the multiple-depot case. The algorithms are both based on a combination of column generation and Lagrangian relaxation. Furthermore, we compare those integrated approaches with each other and with the traditional sequential one on random generated as well as real-world data instances for a suburban/extra-urban mass transit system. To simulate such a transit system, we propose a new way of generating randomly data instances such that their properties are the same as for our real-world instances

Delay Management in Public Transportation: Service Regularity Issues and Crew Re-scheduling

In this paper, we propose a decision support tool to assist a local public transportation company in tackling service delays and small disruptions. We discuss different ways to assess and improve the regularity of the service, and we propose a simulation based optimization system that can be effectively used in a real-time environment taking into account both vehicle and driver shifts. In particular, we describe a tabu-search procedure for the online vehicle scheduling optimizing the regularity of the service and a column generation approach for the consequential crew re-scheduling minimizing the driver extra-time. As a case study, we analyze the management of urban surface lines of Azienda Trasporti Milanese (ATM) of Milan. In the last part of the paper we report a detailed analysis of the experimental phase showing the effectiveness of the proposed approach

Solution Approaches for Vehicle and Crew Scheduling with Electric Buses

The use of electric buses is expected to rise due to its environmental benefits. However, electric vehicles are less exible than conventional diesel buses due to their limited driving range and longer recharging times. Therefore, scheduling electric vehicles adds further operational dificulties. Additionally, various labor regulations challenge public transport companies to find a cost-effcient crew schedule. Vehicle and crew scheduling problems essentially define the cost of operations. In practice, these two problems are often solved sequentially. In this paper, we introduce the integrated electric vehicle and crew scheduling problem (E-VCSP). Given a set of timetabled trips and recharging stations, the E-VCSP is concerned with finding vehicle and crew schedules that cover the timetabled trips and satisfy operational constraints, such as limited driving range of electric vehicles and labor regulations for the crew while minimizing total operational cost. An adaptive large neighborhood search that utilizes branch-and-price heuristics is proposed to tackle the E-VCSP. The proposed method is tested on real-life instances from public transport companies in Denmark and Sweden that contain up to 1,109 timetabled trips. The heuristic approach provides evidence of improving efficiency of transport systems when the electric vehicle and crew scheduling aspects are considered simultaneously. By comparing to the traditional sequential approach, the heuristic finds improvements in the range of 1.17-4.37% on average. A sensitivity analysis of the electric bus technology is carried out to indicate its implications for the crew schedule and the total operational cost. The analysis shows that the operational cost decreases with increasing driving range (120 to 250 kilometers) of electric vehicles

Delay and disruption management in local public transportation via real-time vehicle and crew re-scheduling: a case study

Local public transport companies, especially in large cities, are facing every day the problem of managing delays and small disruptions. Disruption management is a well-established practice in airlines and railways. However, in local public transport the approaches to these problems have followed a different path, mainly focusing on holding and short-turning strategies not directly associated with the driver scheduling. In this paper we consider the case of the management of urban surface lines of Azienda Trasporti Milanese (ATM) of Milan. The main issues are the service regularity as a measure of the quality of service, and the minimization of the operational costs due to changes in the planned driver scheduling. We propose a simulation-based optimization system to cope with delays and small disruptions that can be effectively used in a real-time environment and takes into account both vehicle and driver scheduling. The proposed approach is tested on real data to prove its actual applicability

Applying an Integrated Approach to Vehicle and Crew Scheduling in Practice

This paper deals with a practical application of an integrated approach to vehicle and crew scheduling, that we have developed previously. Computational results have shown that our approach can be applied to problems of practical size. However, application of the approach to the actual problems that one encounters in practice, is not always straightforward. This is mainly due to the existence of particular constraints that can be regarded as \\house rules" of the public transport company under consideration. In this paper we apply our approach to problems of individual bus lines of the RET, the Rotterdam public transport company, where particular constraints should be satisfied. Furthermore, we investigate the impact of allowing drivers to change vehicle during a break. Currently, the rule at the RET is that such changeovers are only allowed in split duties; they are never allowed in other type of duties. We show that it is already possible to save crews if for the non-split duties, restricted changeovers are allowed