Data driven spatio-temporal analysis of e-cargo bike network in Lisbon and its expansion: The Yoob case study

The adoption of more environmentally friendly and sustainable fleets for last-mile parcel delivery within large urban centers has been on the rise. Cargo bikes have been the most common alternative. The implementation of this type of fleet has proven to bring benefits, but has evidenced some limitations. The infrastructure network, which supports urban logistics, had to adapt to respond to the requirements of this new type of fleet. The implementation of micro-hubs and nano-hubs was the solution. Our study has two main objectives. The first objective is to perform a spatiotemporal characterization of fleet behavior, by conducting a case study where we explored the data from YOOB (a last mile delivery logistics start-up that operates in the Lisbon area and outskirts) e-cargo bike fleet. And the second is to identify potential expansion locations to the establishment of new hubs. The work procedures followed the CRIPS-DM methodology and the collected data was based on a 4-month period (January to April 2022). By adopting data science and machine learning techniques, five types of performances of YOOB fleet were identified, with variations in distances traveled, times, volumes transported and speeds. In the perspective of expanding YOOB's e-cargo bike network, three new locations in Lisbon were signaled for potential new hub installation.A adoção de frotas mais ecológicas e sustentáveis para a distribuição das encomendas na última milha dentro dos grandes centros urbanos tem vindo a crescer. As bicicletas de carga têm sido a alternativa mais comum. A implementação deste tipo de frotas, demonstrou trazer benefícios, mas evidenciou algumas limitações. A rede de infraestruturas, que serve de suporte á logística urbana, teve de se adaptar para poder responder às necessidades deste novo tipo de frotas. A implementação de microhubs e nano-hubs foram a alternativa. O nosso estudo tem dois objetivos principais. O primeiro objetivo é o de fazer uma caracterização espácio temporal dos comportamentos da frota, através de um estudo de caso onde efetuámos a exploração dos dados da frota de e-cargo bike da YOOB (start-up logística de entregas na última milha que atua na área de Lisboa e na periferia). E o segundo consiste em identificar potenciais locais de expansão para a instalação de novos hubs no mesmo estudo de caso. Nos processos de trabalho foi seguida a metodologia CRISP-DM e os dados recolhidos foram referentes a um período de 4 meses (Janeiro a Abril de 2022). Com recurso a técnicas de ciência dos dados e aprendizagem automática, foram identificados cinco tipos de desempenhos da frota da YOOB, com variações em distâncias percorridas, tempos efetuados, volumes transportados e velocidades praticadas. Numa perspetiva de expansão da rede de e-cargo bike da YOOB, forma identificados três novos locais na cidade de Lisboa para a instalação potencial de novos hubs

Vehicle Routing Problems: Decision Support Systems and Distributed Approaches

Modern logistics received increasing attention for planning and scheduling operations of transport systems that have to be resource efficient, environmentally sustainable, and compatible with workers\u2019 rights. In particular, modern timeliness requirements and technological advances respectively call for and enable new formulations and solutions for the classical vehicle routing problem (VRP). Indeed, companies and service supplier need of real-time data and fast procedure to face uncertainty and meet people\u2019s expectative, and Information Communication Technologies make this information increasingly available. In other word, some topics emerge: dynamic VRP (DVRP), need of decision support systems (DSS), distributed approaches, balancing workloads for drivers. Firstly, the thesis exposes a review of recent contributions about DVRP, enlightening classifications by source of dynamism (factor of uncertainty), applications, methodologies. A particular attention is paid to distributed approaches, which still represent a minority part of literature. Secondly, due to the complexity and the urgency character of real-world application, the thesis proposes an architecture for a Decision Support System (DSS) that includes a fast VRP module devoted to critical services in city logistics, such as waste collection. The module can be fed with data that are tailored on different scenarios and can be customized for different logistics services. The core of the module is a two-phase heuristic algorithm able to solve a VRP with work shifts constraints for a waste collection service involving large network of pick-up locations. The algorithm is assessed by comparisons with Mixed Integer Linear Problems (MILP) and by the application to real case studies. Thirdly, the thesis proposes a distributed approach for VRP with time windows constraints (VRPTW) in a static and dynamic setting, which also takes in account workload balancing. In particular, the distributed approach is applied to a VRPTW and a multi-depot VRPTW (MDVRPTW), which can respectively act as the initial component and the ongoing component of a DVRP, in which the source of dynamism is the arrival of new service requests. The general strategy is the "cluster first, route second" and the core of the approach consists of an asynchronous, randomized and distributed algorithm. More precisely, vehicles reach the final assignment by iteratively solving local Graph Partitioning problems, in the form of Local-Integer Linear Programming problems (L-ILP), with randomly selected neighbor agents. Afterwards, each vehicle can optimize the route into its own cluster, by solving a small instance of the Traveling Salesman Problem with Time Windows. The proposed approach is assessed for both VRPTW and MDVRPTW by comparisons with exact and centralized approaches with particular regard to balanced workloads in terms of average traveling times, average vehicle loads and their standard deviations. Moreover, an example inspired by a transport company shows the applicability of the proposed approach in real-world scenarios

Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010

This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb. UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010. The overarching theme this year was “Global Challenges”, with specific focus on the following themes: * Crime and Place * Environmental Change * Intelligent Transport * Public Health and Epidemiology * Simulation and Modelling * London as a global city * The geoweb and neo-geography * Open GIS and Volunteered Geographic Information * Human-Computer Interaction and GIS Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond

AI Knowledge Transfer from the University to Society

AI Knowledge Transfer from the University to Society: Applications in High-Impact Sectors brings together examples from the "Innovative Ecosystem with Artificial Intelligence for Andalusia 2025" project at the University of Seville, a series of sub-projects composed of research groups and different institutions or companies that explore the use of Artificial Intelligence in a variety of high-impact sectors to lead innovation and assist in decision-making. Key Features Includes chapters on health and social welfare, transportation, digital economy, energy efficiency and sustainability, agro-industry, and tourism Great diversity of authors, expert in varied sectors, belonging to powerful research groups from the University of Seville with proven experience in the transfer of knowledge to the productive sector and agents attached to the Andalucía TECH Campu