Scheduling Bidirectional Traffic on a Path

We study the fundamental problem of scheduling bidirectional traffic along a path composed of multiple segments. The main feature of the problem is that jobs traveling in the same direction can be scheduled in quick succession on a segment, while jobs in opposing directions cannot cross a segment at the same time. We show that this tradeoff makes the problem significantly harder than the related flow shop problem, by proving that it is NP-hard even for identical jobs. We complement this result with a PTAS for a single segment and non-identical jobs. If we allow some pairs of jobs traveling in different directions to cross a segment concurrently, the problem becomes APX-hard even on a single segment and with identical jobs. We give polynomial algorithms for the setting with restricted compatibilities between jobs on a single and any constant number of segments, respectively

Medical-grade honey enriched with antimicrobial peptides has enhanced activity against antibiotic-resistant pathogens

Honey has potent activity against both antibiotic-sensitive and -resistant bacteria, and is an interesting agent for topical antimicrobial application to wounds. As honey is diluted by wound exudate, rapid bactericidal activity up to high dilution is a prerequisite for its successful application. We investigated the kinetics of the killing of antibiotic-resistant bacteria by RS honey, the source for the production of Revamil® medical-grade honey, and we aimed to enhance the rapid bactericidal activity of RS honey by enrichment with its endogenous compounds or the addition of antimicrobial peptides (AMPs). RS honey killed antibiotic-resistant isolates of Pseudomonas aeruginosa, Staphylococcus epidermidis, Enterococcus faecium, and Burkholderia cepacia within 2 h, but lacked such rapid activity against methicillin-resistant S. aureus (MRSA) and extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli. It was not feasible to enhance the rapid activity of RS honey by enrichment with endogenous compounds, but RS honey enriched with 75 μM of the synthetic peptide Bactericidal Peptide 2 (BP2) showed rapid bactericidal activity against all species tested, including MRSA and ESBL E. coli, at up to 10–20-fold dilution. RS honey enriched with BP2 rapidly killed all bacteria tested and had a broader spectrum of bactericidal activity than either BP2 or honey alone

Integration of railway line planning and timetabling

status: publishe

Integrating robust timetabling in line plan optimization for railway systems

We propose a heuristic algorithm to build a railway line plan from scratch that minimizes passenger travel time and operator cost and for which a feasible and robust timetable exists. A line planning module and a timetabling module work iteratively and interactively. The line planning module creates an initial line plan. The timetabling module evaluates the line plan and identifies a critical line based on minimum buffer times between train pairs. The line planning module proposes a new line plan in which the time length of the critical line is modified in order to provide more flexibility in the schedule. This flexibility is used during timetabling to improve the robustness of the railway system. The algorithm is validated on the DSB S-tog network of Copenhagen, which is a high frequency railway system, where overtakings are not allowed. This network has a rather simple structure, but is constrained by limited shunt capacity. While the operator and passenger cost remain close to those of the initially and (for these costs) optimally built line plan, the timetable corresponding to the finally developed robust line plan significantly improves the minimum buffer time, and thus the robustness, in eight out of ten studied cases.publisher: Elsevier articletitle: Integrating robust timetabling in line plan optimization for railway systems journaltitle: Transportation Research Part C: Emerging Technologies articlelink: http://dx.doi.org/10.1016/j.trc.2017.01.015 content_type: article copyright: © 2017 Elsevier Ltd. All rights reserved.status: publishe

Solution Approaches for Integrated 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 flexible than conventional diesel buses due to their limited driving range and longer recharging times. Therefore, scheduling electric vehicles adds further operational difficulties. Additionally, various labor regulations challenge public transport companies to find a cost-efficient 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 1109 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 (120–250 km) of electric vehicles

Trains do not vanish: the ROADEF/EURO challenge 2014

International audienceThe ROADEF/EURO challenge is a contest jointly organized by the French Operational Research and Decision Aid society (ROADEF) and the European Operational Research society (EURO). The contest has appeared on a regular basis since 1999 and always concerns an applied optimization problem proposed by an industrial partner. The 2014 edition of the ROADEF/EURO challenge was led by the Innovation & Research department of SNCF, a global leader in passenger and freight transport services, and infrastructure manager of the French railway network. The objective of the challenge was to find the best way to store and move trains on large railway sites, between their arrivals and departures. Since trains never vanish and traffic continues to increase, in recent years some stations have been having real congestion issues. Train management in large railway sites is of high interest for SNCF, which is why it was submitted to the operations research community as the industrial problem for the 2014 edition of the ROADEF/EURO challenge. This paper introduces the special section of the Annals of Operations Research volume devoted to the ROADEF/EURO challenge 2014, as well as the methods of the finalist teams and their results

Overview of optimization models and algorithms for train platforming problem

In this paper, an overview of recent advances in the research on train platforming problem (TPP) is presented. The TPP is usually the last problem encountered in planning a railway system which occurs after a schedule of trains in a railway network (train timetable) has been determined. It aims to map a given train timetable to an existing station infrastructure. This process is critical as it determines the feasibility of an optimally generated train timetable along a railway line at station(s) to be visited by trains on the timetable. This optimization problem is in most stations solved manually, and it is a time consuming and error-prone process. Several computer programs are now being developed to aid infrastructure managers and train operators as decision support systems in solving this problem. This paper presents some of these solutions. However, due to variations in operating policies of railway industries in different countries, several variants of this problem exist in the literature. These variations could be seen in the solution approach through the importance attached to level of service, safety of operations, capacity utilization, etc. These variations and the various optimization techniques adopted by researchers are also discussed in this paper. Currently, most models and algorithms presented in literature are not ready for use as commercial systems. Integrating such systems into real-life planning and operations is crucial for efficient use of railway systems