Train unit scheduling with bi-level capacity requirements

Train unit scheduling concerns the assignment of train unit vehicles to cover all the journeys in a fixed timetable allowing the possibility of coupling and decoupling to achieve optimal utilization while satisfying passenger demands. While the scheduling methods usually assume unique and well-defined train capacity requirements, in practice most UK train operators consider different levels of capacity provisions. Those capacity provisions are normally influenced by information such as passenger count surveys, historic provisions and absolute minimums required by the authorities. In this paper, we study the problem of train unit scheduling with bi-level capacity requirements and propose a new integer multicommodity flow model based on previous researches. Computational experiments on real-world data show the effectiveness of our proposed methodology

An integer fixed-charge multicommodity flow (FCMF) model for train unit scheduling

An integer fixed-charge multicommodity flow (FCMF) model is used as the first part of a two-phase approach for train unit scheduling, and solved by an exact branch- and-price method. To strengthen knapsack constraints and deal with complicated scenarios arisen in the integer linear program (ILP) from the integer FCMF model, preprocessing is used by computing convex hulls of sets of points representing all possible train formations utilizing multiple unit types

Fuzzy-logic controlled genetic algorithm for the rail-freight crew-scheduling problem

AbstractThis article presents a fuzzy-logic controlled genetic algorithm designed for the solution of the crew-scheduling problem in the rail-freight industry. This problem refers to the assignment of train drivers to a number of train trips in accordance with complex industrial and governmental regulations. In practice, it is a challenging task due to the massive quantity of train trips, large geographical span and significant number of restrictions. While genetic algorithms are capable of handling large data sets, they are prone to stalled evolution and premature convergence on a local optimum, thereby obstructing further search. In order to tackle these problems, the proposed genetic algorithm contains an embedded fuzzy-logic controller that adjusts the mutation and crossover probabilities in accordance with the genetic algorithm’s performance. The computational results demonstrate a 10% reduction in the cost of the schedule generated by this hybrid technique when compared with a genetic algorithm with fixed crossover and mutation rates

Station level refinement of train unit network flow schedules

Train unit scheduling at the network level focuses on vehicle flows to cover a timetable satisfying seat demands at minimum operational costs. Train stations are simplified to single points ignoring tracks and platforms. Where a trip is covered by coupled train units, the coupling order is also left undetermined. In this paper, the train station simplifications and unit coupling orders are addressed to refine a network flow schedule with added operational plans at the station level

Psychometric properties of the caregiver inventory for measuring caregiving self-efficacy of caregivers of patients with palliative care needs

Taking care of patients with palliative care needs could be a stressful event. While caregiving was associated with decreases in psychological health in caregivers, increased caregiving self-efficacy associated with reduced burden. Yet, there is no instrument available in Chinese for assessing caregiving self-efficacy in the palliative care setting. This study aimed to examine the psychometric properties of a Chinese version of Caregiver Inventory (CGI) in Chinese caregivers of patients with palliative care needs. The CGI was translated to the Chinese language, validated by an expert panel, and tested. A convenience sample of 232 patient-caregiver dyads recruited from three hospitals in Hong Kong was included in the analysis. A high completion rate of 95.5% in caregivers and no floor or ceiling effects were noted for the CGI. In contrast to the four-factor structure identified in the original 21- item CGI, our EFA produced an 18-item solution accounting for 57% of the total variation comprising three factors: (1) Care of the care recipient, (2) Managing information and self-care, and (3) Managing emotional interaction with care recipient (C-CGI-18). Separate dimensions for Managing information and Self-care were not supported. For the three domains of the C-CGI-18, Cronbach’s alphas ranged from 0.84 to 0.90 and 2-week testretest reliability ranged from 0.71 to 0.76. Correlations of the three domains with caregiver strain (r: -0.31 to -0.42, p-values<0.01) and total scores in perceived social support (r: 0.24 to 0.36, p-values<0.01). Correlation between the Care of the care recipient domain and patient’s physical functioning (r=0.17, p-value<0.05) indicated acceptable construct validity. In conclusion, the C-CGI-18 has suitable factor structure and psychometric properties for use in assessing caregiving self-efficacy among Chinese caregivers of patients with palliative care needs. It is simply and easy to use and can be recommended for clinical and research practice for the Hong Kong Chinese populations

First year of 24/7 Acute Stroke Unit. Part 1: eligibility and utilisation of intravenous thrombolysis

INTRODUCTION: Intravenous recombinant tissue plasminogen activator (IV-rtPA) is the standard therapy for acute ischaemic stroke. Because of its narrow therapeutic time window, eligibility and utilisation rates of this treatment remained low. Our IV-rtPA programme was enhanced to a 24/7 protocol since September 20…published_or_final_versio

First year of 24/7 Acute Stroke Unit. Part 2: outcome of stroke thrombolysis using telemedicine

OBJECTIVE: To evaluate the safety and efficacy of intravenous recombinant tissue plasminogen activator (IV-rtPA) for acute ischaemic stroke through telemedicine consultation …published_or_final_versio

Crew Scheduling for Netherlands Railways: "destination: customer"

: In this paper we describe the use of a set covering model with additional constraints for scheduling train drivers and conductors for the Dutch railway operator NS Reizigers. The schedules were generated according to new rules originating from the project "Destination: Customer" ("Bestemming: Klant" in Dutch). This project is carried out by NS Reizigers in order to increase the quality and the punctuality of its train services. With respect to the scheduling of drivers and conductors, this project involves the generation of efficient and acceptable duties with a high robustness against the transfer of delays of trains. A key issue for the acceptability of the duties is the included amount of variation per duty. The applied set covering model is solved by dynamic column generation techniques, Lagrangean relaxation and powerful heuristics. The model and the solution techniques are part of the TURNI system, which is currently used by NS Reizigers for carrying out several analyses concerning the required capacities of the depots. The latter are strongly influenced by the new rules

A two-phase approach for real-world train unit scheduling

A two-phase approach for the train unit scheduling problem is proposed. The first phase assigns and sequences train trips to train units temporarily ignoring some station infrastructure details. Real-world scenarios such as compatibility among traction types and banned/restricted locations and time allowances for coupling/ decoupling are considered. Its solutions would be near-operable. The second phase focuses on satisfying the remaining station detail requirements, such that the solutions would be fully operable. The first phase is modeled as an integer fixed-charge multicommodity flow (FCMF) problem. A branch-and-price approach is proposed to solve it. Experiments have shown that it is only capable of handling problem instances within about 500 train trips. The train company collaborating in this research operates over 2400 train trips on a typical weekday. Hence, a heuristic has been designed for compacting the problem instance to a much smaller size before the branch-and-price solver is applied. The process is iterative with evolving compaction based on the results from the previous iteration, thereby converging to near-optimal results. The second phase is modeled as a multidimensional matching problem with a mixed integer linear programming (MILP) formulation. A column-and-dependentrow generation method for it is under development