Models for the schedule optimization problem at a public transit terminal

This work deals with the proposal of some models for the schedule optimization problem for public transit networks. In particular, we consider the case of a transit terminal where passengers are supposed to split among different lines of a service, or even change mode of transportation in case of intermodal systems. Starting from a given schedule for the transit lines arriving at the terminal, the aim is to decide the optimal schedule for the output lines, in such a way to balance the operative costs of the service and the passenger waiting time at the transit terminal. We propose two different models for this problem, which present strong similarities with some well known combinatorial optimization models. Computational results are also presented, showing the suitability of the models to solve real case studies

Modeling dry-port-based freight distribution planning

In this paper we review the dry port concept and its outfalls in terms of optimal design and management of freight distribution. Some optimization challenges arising from the presence of dry ports in intermodal freight transport systems are presented and discussed. Then we consider the tactical planning problem of defining the optimal routes and schedules for the fleet of vehicles providing transportation services between the terminals of a dry-port-based intermodal system. An original service network design model based on a mixed integer programming mathematical formulation is proposed to solve the considered problem. An experimental framework built upon realistic instances inspired by regional cases is described and the computational results of the model are presented and discussed

Advanced network connectivity features and zonal requirements in covering location problems

Real-world facility planning problems often require to tackle simultaneously network connectivity and zonal requirements, in order to guarantee an equitable provision of services and an efficient flow of goods, people and information among the facilities. Nonetheless, such challenges have not been addressed jointly so far. In this paper we explore the introduction of advanced network connectivity features and spatial-related requirements within Covering Location Problems. We adopt a broad modelling perspective, accounting for structural and economic aspects of connectivity features, while allowing the choice for one or more facilities to serve the facility networks as depots, and containing the maximal distance between any active facility and such depot(s). A novel class of Multi-objective Covering Location problems are proposed, utilising Mixed Integer Linear Programming as a modelling tool. Aiming at obtaining efficiently the arising Pareto Sets and providing actionable decision-making support throughout real planning processes, we adapt to our problem the robust variant of the AUGMEnted ɛ -CONstraint method (AUGMECON-R). Furthermore, we exploit the mathematical properties of the proposed problems to design tailored Matheuristic algorithms which boost the scalability of the solution method, with particular reference to the case of multiple depots. By conducting a comprehensive computational study on benchmark instances, we provide a thorough proof of concept for the novel problems, highlighting the challenging nature of the advanced connectivity features and the scalability of the proposed Matheuristics. From a managerial standpoint, the suitability of the proposed work in responding effectively to the motivating needs is showcased

A hybrid modified-NSGA-II VNS algorithm for the Multi-Objective Critical Disruption Path Problem

This paper considers a Multiple Objective variant of the Critical Disruption Path problem to extend its suitability in a range of security operations relying on path-based network interdiction, including flight pattern optimisation for surveillance. Given a pair of nodes s and t from the network to be monitored, the problem seeks for loopless s - t paths such that, within the induced subgraph obtained via deletion of the path, the size of the largest connected component is minimised, the number of connected components is maximised, while concurrently reducing as much as possible the cost of such disruption path. These three objectives are possibly in conflict with each other, and the scope of this work is to allow for an efficient and insightful approximation of the Pareto front, looking for a trade-off between costs and effectiveness to secure the most convenient paths for security and surveillance operations. We first introduce and formulate the Multi-Objective Critical Disruption Path Problem (Multi-Objs-CDP) as a mixed integer programming formulation (MO-CDP), then we propose an original evolutionary metaheuristic algorithm hybridising modified-NSGA-II and VNS for finding an approximation of the Pareto front, as well as a procedure securing the efficient generation of a high quality pool of initial solutions. The experimental performance of the proposed algorithm, as compared with a variety of competing approaches, proves to be fully satisfactory in terms of time efficiency and quality of the solutions obtained on a set of medium to large benchmark instances

On carriers collaboration in hub location problems

This paper considers a hub location problem where several carriers operate on a shared network to satisfy a given demand represented by a set of commodities. Possible cooperative strategies are studied where carriers can share resources or swap their respective commodities to produce tangible cost savings while fully satisfying the existing demand. Three different collaborative policies are introduced and discussed, and mixed integer programming formulations are provided for each of them. Theoretical analyses are developed in order to assess the potential savings of each model with respect to traditional non-collaborative approaches. An empirical performance comparison on state-of-art sets of instances offers a complementary viewpoint. The influence of several diverse problem parameters on the performance is analyzed to identify those operational settings enabling the highest possible savings for the considered collaborative hub location models. The number of carriers and the number of open hubs have shown to play a key role; depending on the collaborative strategy, savings of up to 50% can be obtained as the number of carriers increases or the number of open hubs decreases

Network Interdiction through Length-Bounded Critical Disruption Paths: a Bi-Objective Approach

In this paper the Bi-Objective k-Length-Bounded Critical Disruption Path (BO-kLB-CDP) optimization problem is proposed, aimed at maximizing the interdiction effects provided on a network by removing a simple path connecting a given source and destination whose length does not exceed a certain threshold. The BO-kLB-CDP problem extends the Critical Disruption Path (CDP) problem introduced by Granata et al. in [Granata, D. and Steeger, G. and Rebennack, S., Network interdiction via a Critical Disruption Path: Branch-and-Price algorithms, Computers & Operations Research, Volume 40, Issue 11, November 2013, Pages 2689–2702]. Several real applications of this class of optimization problems arise in the field of security, surveillance, transportation and evacuation operations. In order to overcome some limits of the original CDP problem and increase its suitability for practical purposes, first we consider a length limitation for Critical Disruption Paths. Second, we generalize the concept of network interdiction considered in the CDP: beside minimizing the cardinality of the maximal connected component after the removal of the CDP, now we are also interested in maximizing the number of connected components in the residual graph. A Mixed Integer Programming formulation for the BO-kLB-CDP problem is therefore proposed and discussed, presenting the results of a multiple objective analysis performed through a computational experience on a large set of instances

A game-theoretic multi-stakeholder model for cost allocation in urban consolidation centres

Recently, many European local authorities have set up Urban Consolidation Centres (UCC) for dealing with challenges arising from the environmental and social impacts of logistical activities in urban contexts through shipment synchronisation and carrier coordination policies. However, the number of successful UCC projects led by local authorities in Europe is low, with most of the UCCs failing to achieve financial sustainability after the initial experimental phase, which is often heavily supported by public funds. In order to propose mechanisms that could favour the economic and financial sustainability of UCC systems, this research develops an adaptation of game-theoretic approaches to the problems of responsibility and cost allocation among stakeholders participating in a UCC delivery network. A solution based on the Shapley Value concept is employed to derive cost allocations; applications of the model to a real-world scenario are evaluated. An extensive sensitivity analysis shows that the proposed cost allocation rules can provide alternative arrangements, based on extended responsibility concepts, which can alleviate the burden on local authorities for the set up of UCCs. As such, results provide useful policy and practice implications on how to safeguard UCCs’ viability under different scenarios, including the outsourcing of the last-mile deliveries

Prevalence and clinical significance of acquired left coronary artery fistulas after surgical myectomy in patients with hypertrophic cardiomyopathy

ObjectivesThe relevance of iatrogenic left coronary artery fistulas complicating surgical myectomy in patients with hypertrophic cardiomyopathy is not known. We prospectively defined the echocardiographic features, prevalence, and clinical significance of left coronary artery fistulas in 40 consecutive patients with hypertrophic cardiomyopathy undergoing extended septal myectomy.MethodsEchocardiographic analysis was performed preoperatively and 1 and 6 months after surgical intervention. Diagnosis of left coronary artery fistulas required evidence of diastolic flow draining from the left ventricular wall into the left ventricular cavity according to prespecified criteria.ResultsLeft coronary artery fistulas were detected in 9 (23%) of the 40 study patients as a single occurrence in all except 1 patient, who had multiple fistulas. At 6 months, left coronary artery fistulas could still be detected in only 2 of the 9 patients. Of these, 1 patient remained asymptomatic but continued to show left coronary artery fistula persistence at 37 months postoperatively. The other, a woman with prior alcohol septal ablation, had progressive severe symptoms that required percutaneous closure of the fistula with a covered stent after angiographic identification of a large first septal branch fistula associated with distal left anterior descending coronary artery steal.ConclusionsIn patients with hypertrophic cardiomyopathy, left coronary artery fistulas are common in the early period after surgical myectomy, although their echocardiographic prevalence is dependent on operator awareness. Most left coronary artery fistulas heal spontaneously. Occasionally, however, fistulas can persist and cause symptoms requiring therapeutic intervention

Methodological approach for the assessment of ultrasound reproducibility of cardiac structure and function: a proposal of the study group of Echocardiography of the Italian Society of Cardiology (Ultra Cardia SIC) Part I

When applying echo-Doppler imaging for either clinical or research purposes it is very important to select the most adequate modality/technology and choose the most reliable and reproducible measurements. Quality control is a mainstay to reduce variability among institutions and operators and must be obtained by using appropriate procedures for data acquisition, storage and interpretation of echo-Doppler data. This goal can be achieved by employing an echo core laboratory (ECL), with the responsibility for standardizing image acquisition processes (performed at the peripheral echo-labs) and analysis (by monitoring and optimizing the internal intra- and inter-reader variability of measurements). Accordingly, the Working Group of Echocardiography of the Italian Society of Cardiology decided to design standardized procedures for imaging acquisition in peripheral laboratories and reading procedures and to propose a methodological approach to assess the reproducibility of echo-Doppler parameters of cardiac structure and function by using both standard and advanced technologies. A number of cardiologists experienced in cardiac ultrasound was involved to set up an ECL available for future studies involving complex imaging or including echo-Doppler measures as primary or secondary efficacy or safety end-points. The present manuscript describes the methodology of the procedures (imaging acquisition and measurement reading) and provides the documentation of the work done so far to test the reproducibility of the different echo-Doppler modalities (standard and advanced). These procedures can be suggested for utilization also in non referall echocardiographic laboratories as an "inside" quality check, with the aim at optimizing clinical consistency of echo-Doppler data

A matheuristic approach for the Quickest Multicommodity k-Splittable Flow Problem

The literature on k-splittable flows, see Baier et al. (2002), provides evidence on how controlling the number of used paths enables practical applications of flows optimization in many real-world contexts. Such a modeling feature has never been integrated so far in Quickest Flows, a class of optimization problems suitable to cope with situations such as emergency evacuations, transportation planning and telecommunication systems, where one aims to minimize the makespan, i.e. the overall time needed to complete all the operations, see Pascoal et al. (2006). In order to bridge this gap, a novel optimization problem, the Quickest Multicommodity k-Splittable Flow Problem (QMCkSFP) is introduced in this paper. The problem seeks to minimize the makespan of transshipment operations for given demands of multiple commodities, while imposing restrictions on the maximum number of paths for each single commodity. The computational complexity of this problem is analyzed, showing its NP-hardness in the strong sense, and an original Mixed-Integer Programming formulation is detailed. We propose a matheuristic algorithm based on a hybridized Very Large-Scale Neighborhood Search that, utilizing the presented mathematical formulation, explores multiple search spaces to solve efficiently large instances of the QMCkSFP. High quality computational results obtained on benchmark test sets are presented and discussed, showing how the proposed matheuristic largely outperforms a state-of-the-art heuristic scheme frequently adopted in path-restricted flow problems