Branch-and-Price Solving in G12

The G12 project is developing a software environment for stating and solving combinatorial problems by mapping a high-level model of the problem to an efficient combination of solving methods. Model annotations are used to control this process. In this paper we explain the mapping to branch-and-price solving. G12 supports the selection of specialised subproblem solvers, the aggregation of identical subproblems, automatic disaggregation when required by search, and the use of specialised branching rules. We demonstrate the benefits of the G12 framework on three examples: a trucking problem, cutting stock, and two-dimensional bin packing

The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations

International audienceDue to new regulations and further technological progress in the field of electric vehicles, the research community faces the new challenge of incorporating the electric energy based restrictions into vehicle routing problems. One of these restrictions is the limited battery capacity which makes detours to recharging stations necessary, thus requiring efficient tour planning mechanisms in order to sustain the competitiveness of electric vehicles compared to conventional vehicles. We introduce the Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and recharging stations (E-FSMFTW) to model decisions to be made with regards to fleet composition and the actual vehicle routes including the choice of recharging times and locations. The available vehicle types differ in their transport capacity, battery size and acquisition cost. Furthermore, we consider time windows at customer locations, which is a common and important constraint in real-world routing and planning problems. We solve this problem by means of branch-and-price as well as proposing a hybrid heuristic, which combines an Adaptive Large Neighbourhood Search with an embedded local search and labelling procedure for intensification. By solving a newly created set of benchmark instances for the E-FSMFTW and the existing single vehicle type benchmark using an exact method as well, we show the effectiveness of the proposed approach

The role of operational research in green freight transportation

Recent years have witnessed an increased awareness of the negative external impacts of freight transportation. The field of Operational Research (OR) has, particularly in the recent years, continued to contribute to alleviating the negative impacts through the use of various optimization models and solution techniques. This paper presents the basic principles behind and an overview of the existing body of recent research on ‘greening’ freight transportation using OR-based planning techniques. The particular focus is on studies that have been described for two heavily used modes for transporting freight across the globe, namely road (including urban and electric vehicles) and maritime transportation, although other modes are also briefly discussed

Vers une meilleure intégration des aspects environnementaux dans la planification de la mobilité par les autorités locales

Le transport contribue à différents problèmes environnementaux comme la dégradation de la qualité de l’air et le changement climatique. Pour répondre à ces défis, les technologies peuvent évoluer et les usagers peuvent changer leurs comportements de mobilité. Les pouvoirs publics ont aussi une responsabilité car, à leur échelle, ils définissent des stratégies qui influencent l’offre et les pratiques. La question de recherche soulevée par ce travail est : comment améliorer l’intégration des aspects environnementaux dans la planification de la mobilité par les autorités locales ? « Autorité locale » renvoie aux autorités organisatrices de la mobilité (AOM) qui organisent la mobilité au niveau local en France. Leur périmètre est celui des établissements publics de coopération intercommunale (EPCI), c’est-à-dire, les métropoles, communautés urbaines, communautés d'agglomération (CA) et communautés de communes

A brief survey on hybrid metaheuristics

The combination of components from different algorithms is currently one of most successful trends in optimization. The hybridization of metaheuristics, such as ant colony optimization, evolutionary algorithms, and variable neighborhood search, with techniques from operations research and artificial intelligence plays hereby an important role. The resulting hybrid algorithms are generally labelled hybrid metaheuristics. The rising of this new research field was due to the fact that the focus of research in optimization has shifted form an algorithm-oriented point of view. In this brief survey on hybrid metaheuristics we provide an overview on some of the most interesting and representative developments.Peer ReviewedPostprint (published version

Exploring the Impact of User Preferences on Shared Autonomous Vehicle Modal Split: A Multi-Agent Simulation Approach

International audience; Shared autonomous vehicles are considered to have a transformative impact on future urban transportation and especially Shared Mobility. In order to assess the transport-related impact of this new mode, various models and simulations are under development. The majority of recently proposed simulations are based on activity-based multi-agent approaches. Thanks to the disaggregated level of data in multi-agent simulation, the traveler decision making mechanisms might be individualized according the attributes. In this paper we try to take in advantage of this granularity in order to explore the impact of user preferences on the modal split of shared autonomous vehicles. To illustrate the proposed methodology the transport system of Paris is simulated by using an activity-based multi-agent tool called MATSim. The traveler preferences toward shared autonomous vehicles use are also summarized based on the literature review. Document type: Conference objec

Metaheuristics for solving a multimodal home-healthcare scheduling problem

Abstract We present a general framework for solving a real-world multimodal home-healthcare scheduling (MHS) problem from a major Austrian home-healthcare provider. The goal of MHS is to assign home-care staff to customers and determine efficient multimodal tours while considering staff and customer satisfaction. Our approach is designed to be as problem-independent as possible, such that the resulting methods can be easily adapted to MHS setups of other home-healthcare providers. We chose a two-stage approach: in the first stage, we generate initial solutions either via constraint programming techniques or by a random procedure. During the second stage, the initial solutions are (iteratively) improved by applying one of four metaheuristics: variable neighborhood search, a memetic algorithm, scatter search and a simulated annealing hyper-heuristic. An extensive computational comparison shows that the approach is capable of solving real-world instances in reasonable time and produces valid solutions within only a few seconds

Nucleocapsid-specific T cell responses associate with control of SARS-CoV-2 in the upper airways before seroconversion

Despite intensive research since the emergence of SARS-CoV-2, it has remained unclear precisely which components of the early immune response protect against the development of severe COVID-19. Here, we perform a comprehensive immunogenetic and virologic analysis of nasopharyngeal and peripheral blood samples obtained during the acute phase of infection with SARS-CoV-2. We find that soluble and transcriptional markers of systemic inflammation peak during the first week after symptom onset and correlate directly with upper airways viral loads (UA-VLs), whereas the contemporaneous frequencies of circulating viral nucleocapsid (NC)-specific CD4+ and CD8+ T cells correlate inversely with various inflammatory markers and UA-VLs. In addition, we show that high frequencies of activated CD4+ and CD8+ T cells are present in acutely infected nasopharyngeal tissue, many of which express genes encoding various effector molecules, such as cytotoxic proteins and IFN-γ. The presence of IFNG mRNA-expressing CD4+ and CD8+ T cells in the infected epithelium is further linked with common patterns of gene expression among virus-susceptible target cells and better local control of SARS-CoV-2. Collectively, these results identify an immune correlate of protection against SARS-CoV-2, which could inform the development of more effective vaccines to combat the acute and chronic illnesses attributable to COVID-19

Automated deliveries: The future of urban logistics?

International audienceThe large-scale deployment of connected automated vehicles for goods delivery has yet to be achieved. This chapter will focus on the implementation of automated deliveries in city contexts and will examine the ways in which urban logistics intersect with maritime and inland ports. It will also provide a brief outline of the fundamental technical concepts involved in automated deliveries and highlight the various challenges this sector faces, including environmental concerns, social acceptance, legal considerations, and operational planning for automated vehicle deliveries. This chapter will conclude by offering practical insights and a vision for the future development of automated deliveries, emphasizing the need for a collaborative approach between stakeholders in order to ensure sustainable and liveable urban environments for the generations to come