Distinguishing different types of city tourists through clustering and recursive logit models applied to Wi-Fi data

We discuss the possibilities to distinguish different types of tourists based on Wi-Fi sensor data. The data are obtained from 20 sensors employed in Higashiyama, Kyoto, which is an area highly frequented by tourists. We describe tourist-tours as a sequence of sensors at which they are observed. Based on these records a clustering approach is chosen where we select as clustering variables, among others, the degree of detours and the length of time they are observed. We find that we can distinguish groups of tourists that are visiting a number of sightseeing spots in a short time from others who walk through the area more leisurely and are likely enjoying souvenir shops and restaurants. For the main tourist clusters than a Recursive Logit approach is applied to model their route-choice based on path length and attractions en-route. We find that the estimated parameters reflect these group characteristics

Truckload freight transportation utilizing relay points to improve the driving job

We propose a relay point based approach on a highway transportation network to obtain robust solutions for the truck driver turnover and driver retention problem. We exploit the characteristics of the driver routing problem and truckload freight moved over a highway transportation network and introduce a new approach to route drivers over shorter distances and to move trailers continuously while holistically considering important performance measures as related to the truck driver, transportation carrier, and customer. The amount of time drivers spend driving and the time spent at home are exploited to determine a balance between driver home time and driver pay. A mathematical program is introduced to determine where relay points should be more optimally located to exchange equipment, perform equipment maintenance, access resting facilities, etc. while considering important costs related to transporting truckload freight. The intention is to propose a method to improve the truckload driving job but not at the expense of the transportation carrier and customer. We discuss some of the desirable characteristics of this approach and also investigate the sensitivity of the solutions via a numerical experiment

Crowdsensing-driven route optimisation algorithms for smart urban mobility

Urban rörlighet anses ofta vara en av de främsta möjliggörarna för en hållbar statsutveckling. Idag skulle det dock kräva ett betydande skifte mot renare och effektivare stadstransporter vilket skulle stödja ökad social och ekonomisk koncentration av resurser i städerna. En viktig prioritet för städer runt om i världen är att stödja medborgarnas rörlighet inom stadsmiljöer medan samtidigt minska trafikstockningar, olyckor och föroreningar. Att utveckla en effektivare och grönare (eller med ett ord; smartare) stadsrörlighet är en av de svåraste problemen att bemöta för stora metropoler. I denna avhandling närmar vi oss problemet från det snabba utvecklingsperspektivet av ITlandskapet i städer vilket möjliggör byggandet av rörlighetslösningar utan stora stora investeringar eller sofistikerad sensortenkik. I synnerhet föreslår vi utnyttjandet av den mobila rörlighetsavkännings, eng. Mobile Crowdsensing (MCS), paradigmen i vilken befolkningen exploaterar sin mobilkommunikation och/eller mobilasensorer med syftet att frivilligt samla, distribuera, lokalt processera och analysera geospecifik information. Rörlighetavkänningssdata (t.ex. händelser, trafikintensitet, buller och luftföroreningar etc.) inhämtad från frivilliga i befolkningen kan ge värdefull information om aktuella rörelsesförhållanden i stad vilka, med adekvata databehandlingsalgoriter, kan användas för att planera människors rörelseflöden inom stadsmiljön. Såtillvida kombineras i denna avhandling två mycket lovande smarta rörlighetsmöjliggörare, eng. Smart Mobility Enablers, nämligen MCS och rese/ruttplanering. Vi kan därmed till viss utsträckning sammanföra forskningsutmaningar från dessa två delar. Vi väljer att separera våra forskningsmål i två delar, dvs forskningssteg: (1) arkitektoniska utmaningar vid design av MCS-system och (2) algoritmiska utmaningar för tillämpningar av MCS-driven ruttplanering. Vi ämnar att visa en logisk forskningsprogression över tiden, med avstamp i mänskligt dirigerade rörelseavkänningssystem som MCS och ett avslut i automatiserade ruttoptimeringsalgoritmer skräddarsydda för specifika MCS-applikationer. Även om vi förlitar oss på heuristiska lösningar och algoritmer för NP-svåra ruttproblem förlitar vi oss på äkta applikationer med syftet att visa på fördelarna med algoritm- och infrastrukturförslagen.La movilidad urbana es considerada una de las principales desencadenantes de un desarrollo urbano sostenible. Sin embargo, hoy en día se requiere una transición hacia un transporte urbano más limpio y más eficiente que soporte una concentración de recursos sociales y económicos cada vez mayor en las ciudades. Una de las principales prioridades para las ciudades de todo el mundo es facilitar la movilidad de los ciudadanos dentro de los entornos urbanos, al mismo tiempo que se reduce la congestión, los accidentes y la contaminación. Sin embargo, desarrollar una movilidad urbana más eficiente y más verde (o en una palabra, más inteligente) es uno de los temas más difíciles de afrontar para las grandes áreas metropolitanas. En esta tesis, abordamos este problema desde la perspectiva de un panorama TIC en rápida evolución que nos permite construir movilidad sin la necesidad de grandes inversiones ni sofisticadas tecnologías de sensores. En particular, proponemos aprovechar el paradigma Mobile Crowdsensing (MCS) en el que los ciudadanos utilizan sus teléfonos móviles y dispositivos, para nosotros recopilar, procesar y analizar localmente información georreferenciada, distribuida voluntariamente. Los datos de movilidad recopilados de ciudadanos que voluntariamente quieren compartirlos (por ejemplo, eventos, intensidad del tráfico, ruido y contaminación del aire, etc.) pueden proporcionar información valiosa sobre las condiciones de movilidad actuales en la ciudad, que con el algoritmo de procesamiento de datos adecuado, pueden utilizarse para enrutar y gestionar el flujo de gente en entornos urbanos. Por lo tanto, en esta tesis combinamos dos prometedoras fuentes de movilidad inteligente: MCS y la planificación de viajes/rutas, uniendo en cierta medida los distintos desafíos de investigación. Hemos dividido nuestros objetivos de investigación en dos etapas: (1) Desafíos arquitectónicos en el diseño de sistemas MCS y (2) Desafíos algorítmicos en la planificación de rutas aprovechando la información del MCS. Nuestro objetivo es demostrar una progresión lógica de la investigación a lo largo del tiempo, comenzando desde los fundamentos de los sistemas de detección centrados en personas, como el MCS, hasta los algoritmos de optimización de rutas diseñados específicamente para la aplicación de estos. Si bien nos centramos en algoritmos y heurísticas para resolver problemas de enrutamiento de clase NP-hard, utilizamos ejemplos de aplicaciones en el mundo real para mostrar las ventajas de los algoritmos e infraestructuras propuestas

The Impact of Information and Communication Technology on the Tourism Sector

Information and Communication Technology (ICT) has changed the global businesses environment by a wide range of tools, methodologies and functions, facilitating the strategic management and supporting firms to achieve a long term competitive advantage. The aim of this paper is to provide an overview of the new applications of Information Communication Technology in tourism industry, the contribution of ICT to the promotion of the tourist product, as well as the potential to the tourism management and the process of decision-making. One important tool, which helps in making decisions in the field of tourism economy, is the Geographic Information System (GIS), which provides a comprehensible representation of the statistical figures of the tourism economy by facilitating decision-making on tourism policy. In this paper is presented some tourist financial figures and their visualization through graphs by Geographic Information System

Sustainable development in contract logistics through green warehousing and distribution. Practical case: Maersk warehouse

The thesis is dedicated to the staple part of contract logistics – warehousing and distribution. The nature of this study is to show the sustainable development of (green) warehousing, the crucial changes and achievements in the sector and how these improvements impact the environment and society. The author appeals to the research and analytical methods where he investigates the sources and related documents to analyse the global situation in contract logistics and describe the current situation of green warehousing. The practical method helped to study the Maersk warehouse and to show if it indeed responds to the requirements of sustainable durability as well as highlights the transformations conducting the company towards decarbonisation. The first part dedicated to the general research of warehousing and distribution. The author investigated the main features of warehouse location and its crucial importance, studied different types of layouts, showed the modernisation and application of WMS facilitating the operation’s running, examined the efficiency of equipment usage, light and air conditioning systems and analysed the social impact of warehousing for sustainability. The second chapter observes the practical case of Maersk warehouse as the first logistic centre for the company in Iberia area. The author not only investigated the main features of warehouse, but also showed how the company is implementing the sustainable tools to reduce the environmental impact as well as gave at the glace the future of warehousing via innovation and technology usage

Attention-Based Neural Network for Solving the Green Vehicle Routing Problem in Waste Management

23.08.23: Trekkes tilbake fra visning som løsning på at oppgaven ble ferdigstilt fra studieadministrasjonen litt for fort/IHTIThe transport sector is a major contributor to the emission of greenhouse gases and air pollution. As urbanization and population growth continue to increase, the demand for transportation services grows, emphasizing the need for sustainable practices. Therefore, incorporating sustainability into the transport sector can effectively reduce its negative impacts on the environment and optimize the utilization of resources. This thesis aims to address this issue by proposing a novel method that integrates neural networks into the development of a green vehicle routing model. By incorporating environmental considerations, particularly fuel consumption, into the optimization process, the model seeks to generate more sustainable route solutions. The integration of machine learning techniques, specifically an attention-based neural network, demonstrates the potential of combining machine learning with operations research for effective route optimization. While the effectiveness of the green vehicle routing problem (GVRP) has been demonstrated in providing sustainable routes, its practical applications in real-world scenarios are still limited. Therefore, this thesis proposes the implementation of the GVRP model in a real-world waste collection routing problem. The study utilizes data obtained from Remiks, a waste management company responsible for waste collection and handling in Tromsø and Karlsøy. The findings of this study highlight the promising synergy between machine learning and operations research for further advancements and real-world applications. Specifically, the application of the GVRP approach to waste management issues has been shown to reduce emissions during the waste collection process compared to routes optimized solely for distance minimization. The attention-based neural network approach successfully generates routes that minimize fuel consumption, outperforming distance-optimized routes. These results underscore the importance of leveraging the GVRP to address environmental challenges while enhancing decision-making efficiency and effectiveness. Overall, this thesis provides insights for developing sustainable and optimized routes for real-world problems

Place, recreation and local development

Proceedings of the 9th International Conference on Monitoring and Management of Visitors in Recreational and Protected Areas (MMV9), Bordeaux, FRA, 29-/08/2018 - 31/08/2018It is our pleasure to welcome you to the 9th international Conference on Monitoring and Management of Visitors in Recreational and Protected Areas (MMV9) with a program including keynote speeches, organized and poster sessions, a half-day field trip, social events and post conference trips. This is the first time that France has hosted an MMV Conference. Our country is ranked as the world's top tourist destination, thanks largely to its culture, art, and gastronomy, as well as popular cities such as Paris and Bordeaux. On the other hand, France's potential as a destination for outdoor recreation and nature-based tourism is not hugely publicized, despite its many unique features in this respect: varied climate and natural assets (shoreline, mountains, lakes, and forests), large expanses of countryside, and a network of protected natural areas, to name but a few. France's protected areas are often free to access for the general public. However, in contrast with other countries, nature conservation in specific areas is much less widespread. Where it does take place, it is often centered on territories that are perceived to be "attractive", and where many conflicting activities are practiced. This may be one of the reasons why contractual tools and regional park systems are quite popular in France. The MMV Conference offers an excellent opportunity to discuss the situation in France in greater depth. The theme proposed for the conference was "recreation, place and local development". This reflects our assumption that recreational areas are not just physical assets designed to receive visitors for the purpose of leisure - which in itself would already be something of great importance - but that they reflect deeper social phenomena, as demonstrated through the range of organized sessions dedicated to discussing questions such as environmental education and economic development, but also emerging themes such as social integration, community resilience, environmental justice, and health. The traditional topics covered by MMV Conference reflect an evolving society: with innovations in monitoring techniques (both on people and nature), focus on new populations (Y generation, ethnic minority) and a larger concern for individual engagement and participative management. The 9th Edition of MMV is co-hosted by Irstea and BSA. This would not have been possible without significant contributions from a large number of additional partners and sponsors as well as our national scientific and organizing committee. We would like to take this opportunity to thank everyone for their help. After two years of planning, we are proud to announce that we have more than 160 presentations from 30 countries, meaning that the conference will host over 200 participants from across the globe. We are honored that the International Steering Committee has given us the opportunity to be part of this great MMV community, which organized its first meeting in 2002. We hope you will enjoy the conference as much as we enjoyed organizing it. If you can't be with us in person, we hope that you will enjoy reading our publications