We present a multi-objective two-echelon vehicle routing problem with vehicle synchronization and "grey zone" customers arising in the context of urban freight deliveries. Inner-city center deliveries are performed by small vehicles due to access restrictions, while deliveries outside this area are carried out by conventional vehicles for economic reasons. Goods are transferred from the first to the second echelon by synchronized meetings between vehicles of the respective echelons. We investigate the assignment of customers to vehicles, i.e., to the first or second echelon, within a so-called "grey Zone" on the border of the inner city and the area around it. While doing this, the economic objective as well as negative external effects of transport, such as emissions and disturbance (negative impact on citizens due to noise and congestion), are taken into account to include objectives of companies as well as of citizens and municipal authorities. Our metaheuristic - a large neighborhood search embedded in a heuristic rectangle/cuboid splitting - addresses this problem efficiently. We investigate the impact of the free assignment of part of the customers ("grey Zone") to echelons and of three different city layouts on the solution. Computational results show that the impact of a "grey Zone" and thus the assignment of these customers to echelons depend significantly on the layout of a city. Potentially pareto-optimal solutions for two and three objectives are illustrated to efficiently support decision makers in sustainable city logistics planning processes.

Traditionally, route planning in the transportation sector has only focused on minimizing the total distance driven when transporting goods or people. This is often done using software tools since planning the optimal route is a complex task that is hard to solve by hand. While driving the shortest distance possible is an effort towards lowering fuel costs, which is one of the largest operating costs for truck transportation companies, it is not necessarily the most fuel efficient route. Recently, research has emerged regarding fuel minimizing route planning in order to perform transport operations at the lowest fuel cost possible. One factor contributing to fuel consumption is vehicle speed, since high speed means high wind resistance. Fuel can therefore be conserved by driving at lower speeds. Though lower speeds means longer travelling time, meaning that if the route is disrupted, causing a delay, there is an increased risk that all tasks cannot be performed during the started working day. The purpose of this thesis is to determine how to plan fuel efficient routes in a transportation system prone to disruptions. It was conducted at Scania to further understand how their truck customers can increase profitability in their businesses by planning fuel efficient routes. The truck transportation business is under heavy pressure with low margins. It is therefore valuable to plan fuel efficient routes. The outcome of this thesis is two linear programming models for route planning that take truck capacity, customer demand and time windows for delivery into account. The first model can be used during planning to find a fuel efficient route in order to deliver to all customers to the lowest fuel cost possible. The model gives a route with predetermined average speeds between the customers, as well as arrival time at each customer. When appropriate, the truck is proposed to drive at a slightly decreased speed, to lower wind resistance and thereby fuel consumption. By also taking load weight into account, the route can be planned such that a heavy part of the load is delivered early, reducing the weight carried for the rest of the route. The proposed model accomplishes on average 6.3 % lower fuel cost, compared to the most commonly used route planning model, where the shortest total driving distance is sought. If something would happen that disrupts the route, it might be impossible to deliver all customers before the day ends. To handle those situations, a second model is proposed. Once the transport is delayed, the model will revise the initial route and propose a new route based on a cost of delaying a delivery. The goal is then to deliver as much as possible to the lowest possible cost. The new route will still consist of predetermined average speeds and arrival times. The proposed model is a tool for handling the complex task of recalculating routes once a disruption occurs. In summary, the first model provides support to plan a route that potentially lowers the operational costs for truck transportation companies. If the planned route is disrupted, the second model will revise it and give a new route with new speeds and arrival times. If possible, the revised route will still result in making all deliveries, otherwise the model will postpone the smallest deliveries to the next day. Together, the two models serve as a valuable support for truck transport companies that want to increase their profitability by lowering their operational costs. / Traditionellt har ruttplanering inom transportsektorn endast fokuserat på att minimera den totala körsträckan vid transport av gods eller människor. Detta görs ofta med hjälp av mjukvaruverktyg, eftersom optimal ruttplanering är en komplex uppgift som är svår att lösa för hand. Att köra den kortaste totalsträckan är ett sätt att sänka bränslekostnaderna, vilket är en av de största driftskostnaderna för lastbilstransportföretag, men det är inte nödvändigtvis den mest bränsleeffektiva rutten. Den senaste tiden har allt mer forskning bedrivits inom bränsleminimering för att kunna utföra transportuppdrag till lägsta möjliga bränslekostnad. En faktor som bidrar till bränsleförbrukningen är fordonets hastighet, eftersom hög hastighet innebär högt luftmotstånd. Bränsleförbrukningen kan därför minskas genom att köra i lägre hastigheter. Även om lägre hastigheter betyder längre körtid, vilket innebär att om rutten störs och lastbilen blir försenad, finns det en ökad risk att allt inte kan levereras under den påbörjade arbetsdagen. Syftet med detta arbete är att bestämma hur bränsleeffektiva rutter kan planeras i ett transportsystem benäget för störningar. Arbetet genomfördes på Scania för att förstå hur deras lastbilskunder kan öka lönsamheten i sina företag genom att planera bränsleeffektivare rutter. Lastbilstransportbranschen är under hög press med låga marginaler. Det är därför värdefullt för Scanias lastbilskunder att planera bränsleeffektiva rutter. Arbetet resulterade i två ruteplaneringsmodeller som tar hänsyn till lastkapacitet, kundbehov och tidsfönster för leverans. Den första modellen kan användas vid planering för att hitta en bränsleeffektiv rutt så att alla kunder levereras till lägsta möjliga bränslekostnad. Modellen ger en rutt med förbestämda genomsnittshastigheter mellan kunderna, såväl som ankomsttid hos varje kund. När det anses lämpligt föreslås något minskade hastigheter, för att minska luftmotståndet och därigenom bränsleförbrukningen. Genom att även ta hänsyn till vikt, kan rutten planeras så att en tung del av lasten levereras tidigt, vilket minskar den vikt som transporteras på resterande sträckor. Den föreslagna modellen uppnår i genomsnitt 6,3% lägre bränslekostnad jämfört med den vanligaste ruteplaneringsmodellen, som ger den kortaste totala körsträckan. Om något skulle hända som stör rutten kan det vara omöjligt att leverera alla kunder innan dagen slutar. För att hantera dessa situationer föreslås en andra modell. När transporten är försenad planerar modellen om den ursprungliga rutten och föreslår en ny rutt baserat på kostnaden för att skjuta upp en leverans. Målet är då att leverera så mycket som möjligt till lägsta möjliga kostnad. Den nya rutten består fortfarande av förbestämda medelhastigheter och ankomsttider. Genom att använda den föreslagna modellen tillhandahålls ett verktyg för att hantera den komplexa uppgiften att planera om rutten vid en störning. Sammanfattningsvis ger den första modellen stöd för att planera en rutt som potentiellt sänker driftskostnaderna för lastbilstransportföretag. Om den planerade rutten utsätts för en störning, föreslår den andra modellen en ny rutt med nya hastigheter och ankomsttider. Om det är möjligt innebär den nya rutten fortfarande att lastbilen levererar till alla kunder, om inte skjuts de minsta leveranserna upp till nästa dag. Tillsammans är de två modellerna ett värdefullt stöd för lastbilstransportföretag som vill öka lönsamheten genom att sänka sina driftskostnader.

El presente trabajo de investigación tiene como objetivo reducir el índice de devoluciones de una empresa de consumo masivo. Se aplicó la metodología Lean Warehousing y la herramienta VRP para plantear una solución al problema. El proyecto se divide en cuatro capítulos. En el primer capítulo se desarrolla los conceptos y bases teóricas en las que se fundamenta la propuesta. El segundo capítulo presenta el entorno de la empresa, los procesos realizados y los roles que desempeñan cada uno de los trabajadores. También, se identifica el problema a resolver, para ello se requirió utilizar como herramienta el árbol de decisiones para identificar las causas raíz, las cuales son explicadas y fundamentadas. El tercer capítulo plantea 2 metodologías que ayudarán a resolver las 4 causas principales. La primera metodología consiste en determinar la ruta de transporte óptima y la segunda metodología plantea mejorar el abastecimiento y control de productos dentro del almacén. Finalmente, se presenta los costos de la implementación y los beneficios que se obtendrían con la implementación de las propuestas. Por último, el cuarto capítulo se expone los resultados de la implementación con la finalidad de reducir el índice de devoluciones. Así como, la reflexión del proyecto y las recomendaciones para futuras investigaciones. / This research work aims to reduce the rate of returns of a mass consumption company. The Lean Warehousing methodology and the VRP tool were applied to propose a solution to the problem. The project is divided into four chapters. In the first chapter the theoretical concepts and bases on which the proposal is based are developed. The second chapter presents the company's environment, the processes performed and the roles that each of the workers play. Also, the problem to be solved is identified, for this it was required to use the decision tree as a tool to identify the root causes, which are explained and substantiated. The third chapter presents 2 methods to help resolve the 4 main causes. The first methodology consists in determining the optimal transport route and the second methodology proposes to improve the supply and control of products within the warehouse. Finally, the implementation costs and the benefits that would be obtained with the implementation of the proposals are presented. Finally, the fourth chapter describes the results of the implementation in order to reduce the rate of returns. As well as, the reflection of the project and the recommendations for future research. / Trabajo de Suficiencia Profesional

A comprehensive study is presented of the Capacitated Multi DepotGreen Vehicle Routing Problem (CMDGVRP) applied to a heterogeneous fleet of electronic waste collecting vehicles with two objectives: to reduce the total fuel consumption of the vehicles (environmental sustainability) and to limit the continuous drive-time of the drivers (social sustainability). Research has been limited from this aspect, and in this study, the focus is on the practical application of pickup and delivery of electronic waste. The study also presents results for the online dynamic routing variant of this problem, where traffic congestion appears mid-route. A detailed analysis and parameter optimization has been done for Simulated Annealing, Genetic algorithm(GA), along with more advanced variants like Non-dominated Sorting GA (NSGA II), NSGA III, UNSGA III, and Indicator-Based Selection Evolutionary Algorithm (IBEA). Additionally, the Gini index is used to create a multi-objective model, which is novel in the context of CMDGVRP to the best of our knowledge. The use of the Gini index in the field of CMDGVRP shows excellent potential in balancing environmental, economic, and social sustainability. An extension of the CMDGVRP is introduced where vehicles can visit dropoff locations mid-route and then continue with a new route. This implementation is novel to our knowledge and is named Drop-and-continue. It is shown to increase the performance on large datasets. Results are presented from realistic simulation studies on a public dataset, with varying route lengths and vehicle fleet sizes, along with a real-world dataset from a waste collection company in Sweden. The results show that the optimal choice of algorithm depends on the dataset size and if there is a maximum budget of evaluations or computation time. Realistic problems are solved in a matter of a few seconds, given that they are initiated well. Simulated Annealing and Genetic algorithm prove to be very competitive in the case of large problems and limited computation time budget.

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In the literature on B2C logistics of e-commerce, the two main delivery methods - home delivery and delivery to collection-delivery points (CDPs) - have rarely been compared with respect to their environmental effects. This is the case despite a growing e-commerce and the fact that the logistic part of the transportation sector stands for a great amount of the pollution in urban areas. In this report, the two delivery methods have been compared to each other with respect to their environmental impacts through a custom-made network impact model, including simulation using vehicle routing problems (VRPs) and a cross-nested logit model. The results show that one delivery method's advantage over the other (only regarding emissions) is strongly dependent on the distance to the distribution center (DC), the customer density, the density of CDPs and the demographics of that area. Home deliveries proved to be more sensitive to the customer density factor and the distance to the DC than CDP deliveries. / I litteraturen om e-handelslogistik har de två huvudsakliga leveransmetoderna -- hemleverans och leverans till utlämningsställe (CDP) -- sällan jämförts med avseende på deras miljöeffekter. Detta trots en växande e-handel och faktumet att logistikdelen av transportsektorn står för en stor del av föroreningarna i städer. I denna rapport har de två leveransmetoderna jämförts med avseende på deras miljöpåverkan genom en skräddarsydd modell, som bygger dels på simulering med hjälp av ruttplaneringsproblem (VRP) och dels på en korsnästad logitmodell (CNL). Resultaten visar att vilken leveransmetod som presterar bäst (räknat utifrån lägst utsläpp), är starkt beroende av avståndet till distributionscentret (DC), kundtätheten, tätheten av utlämningsställen och områdets demografi. Hemleveranser visade sig vara mer känsliga för kundtätheten och avståndet till distributionscentret än leveranser via utlämningsställe.

Environmental issues are a vital concern in today’s world. The Swedish government and local businesses are developing a sustainable business and eco-friendly environment for city inhabitants. Last-mile pickup and delivery services are a key concern, which significantly impacts the environment and society. The Norwegian/Swedish parcel delivery company Bring, the reusable waste management company Ragn-Sells, the city of Stockholm, the research institute Sustainable Innovation, and the KTH Royal Institute of Technology are jointly working together in the Intercitylog2 project with a vision to handle better last-mile pickups or deliveries that are jointly serviced by small electric vehicles from an urban micro terminal. This thesis addresses the optimizations of simultaneous pickup and delivery operations using homogeneous vehicles and considering vehicle capacity, time windows and environmental constraints. A mathematical model is developed to address the problem using an exact commercial solver. The quality of the solutions has been evaluated with real pickup and deliveries of the participating company. The primary objective function is formulated to minimize the travel cost by finding the shortest path, and the results are compared with current routing operation data. KPIs are developed and evaluated based on the facts and figures from the obtained results of the experiments. The two scenarios, big vehicles and small vehicles are also developed and evaluated to find the best route optimization opportunity for the companies. The results show that the optimized operation could decrease delivery distance by 36.72% and 37.13% and delivery time by 43.65% and 47.08% for big and small vehicles operations, respectively, compared to the current routing operations. A round trip can complete within a defined time frame to avoid the battery running out during a route. Energy constraints demonstrate that using electric vehicles considerably reduce significant amounts of CO2 emission from the environment. / Miljöfrågor är en viktig fråga i dagens värld. Den svenska regeringen och lokala företag arbetar tillsammans för att utveckla ett hållbart företagande och miljövänlig miljö för stadens invånare. Last-mile hämtning och leveranstjänster är en viktig fråga, som avsevärt påverkar miljön och samhället.Det norsk/svenska paketleveransföretaget Bring, återanvändbara avfallshanteringsföretaget Ragn- Sells, Stockholms stad, forskningsinstitutet Sustainable Innovation och Kungliga Tekniska Högskolan arbetar tillsammans i Intercitylog2-projektet för en vision för att bättre hantera last-mile pickuper eller leveranser som gemensamt betjänas av små elfordon från en urban mikroterminal. Detta examensarbete behandlar optimering av samtidiga hämtnings- och leveransoperationer med homogena fordon och med hänsyn till fordonskapacitet, tidsfönster och miljömässiga begränsningar. En matematisk modell utvecklas för att ta itu med problemet med en exakt kommersiell lösare och kvaliteten på lösningarna har utvärderats med verklig upphämtning och leveranser från det deltagande företaget. Den primära målfunktionen är formulerad för att minimera reskostnaden genom att hitta den kortaste vägen, och resultaten jämförs med aktuella ruttoperationsdata. KPI:er utvecklas och utvärderas utifrån fakta och siffror från de erhållna resultaten av experimenten. De två scenarierna, stora fordon och små fordon, är också utvecklade och utvärderade för att hitta den bästa ruttoptimeringsmöjligheten för företagen. Resultaten visar att den optimerade driften kan minska leveransavståndet med 36,72% och 37,13% och leveranstiden med 43,65% och 47,08% för stora och små fordonsoperationer, jämfört med nuvarande ruttoperationer. En tur och retur kan genomföras inom en definierad tidsram för att undvika att batteriet tar slut under en rutt. Energibegränsningar visar att användning av elfordon avsevärt minskar betydande mängder CO2-utsläpp från miljön.

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<p dir="ltr">The escalating frequency and impact of natural disasters have necessitated the study of Humanitarian Logistics (HL) optimization to mitigate human and financial losses. This dissertation encompasses three pivotal studies that collectively seek to address some of the numerous gaps identified in the nascent literature of HL optimization, particularly in conflict-ridden and low-security environments. The first study conducts a comprehensive survey on the application of Multi-Criteria Decision Making (MCDM) methods in HL, identifying a significant gap between academic research and practical challenges, and highlighting underexplored areas within multicriteria optimization in HL. The second study introduces innovative deterministic and possibilistic models to improve the safety and security of humanitarian personnel by developing a vehicle routing model that minimizes the predictability of trips, a novel aspect in HL research. This includes the introduction of the Humanitarian Vehicle Routing Problem with Non-Routineness of Trips (HVRPNRT), creation of a unique index to measure trip routineness and the provision of an approximate closed-form solution for the aid allocation subproblem, and introduces a novel case study from the ongoing civil unrest in South Sudan. The third study presents a novel heuristic solution algorithm for the HVRPNRT, which is the first of its kind, and outperforms the commercial solver CPLEX on some instances. This algorithm offers near-optimal solutions with reduced computational times and maintains feasibility under stringent security conditions, thereby advancing the field of security-aware HL optimization. Collectively, these studies offer significant contributions to the field of HL optimization, providing a recent through survey of the field, novel practical models, methodologies, and an algorithm that address both operational efficiency and security challenges, in an effort to bridge the gap between theoretical research and real-world humanitarian needs.</p>

Submitted by Filipe dos Santos (fsantos@pucsp.br) on 2018-10-19T11:51:51Z No. of bitstreams: 1 Rafael Emídio Murata Rodrigues.pdf: 1071545 bytes, checksum: 468e0f7e27e278e12eed0dd52f4198cc (MD5) / Made available in DSpace on 2018-10-19T11:51:51Z (GMT). No. of bitstreams: 1 Rafael Emídio Murata Rodrigues.pdf: 1071545 bytes, checksum: 468e0f7e27e278e12eed0dd52f4198cc (MD5) Previous issue date: 2018-08-30 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / In our lives, we constantly move in streets and neighborhoods. In general, we consider time and (or distance) when planning the route. However, their solutions may face complex problems arising from the different possibilities of solutions. Similar to route planning, the Vehicle Routing Problem was introduced by George B. Dantzig and John H. Ramser in 1959 and consists of delivering gasoline to several fuel stations; at first a mathematical proposal, later became an algorithmic approach, for planning of routes of delivery of products in an optimized way (searching the "shortest path"). Although, during the search of shortest path, they are limited to the use of the streets. In this context emerges the Human Routing Problem, such an approach is not limited to streets, but makes use of all possible paths, by vehicles and humans. Such a problem can be observed in route planning at airports, museums and a supply chain company that wants to optimize the route of delivery of its products and increase customer satisfaction. Based on the Vehicle Routing Problem, the Human Routing Problem will be proposed. Its problematic will be demonstrated in a prototype, capable of assisting in the planning of human routes and three use cases. Ideas of Human Routing Problem had inspiration in the collective foraging insects / Na nossa vida, nos locomovemos constantemente em ruas e bairros. Em geral, consideramos o tempo e (ou a distância), ao planejar a rota. Contudo, suas soluções podem enfrentar problemas complexos, decorrentes das diversas possibilidades de soluções. Semelhante a planejamento de rotas, o Problema de Roteamento de Veículos foi introduzido por George B. Dantzig, e John H. Ramser em 1959 e consiste em entregar gasolina diversos postos de combustível; a princípio uma proposta matemática, mais tarde tornou-se uma abordagem algorítmica, para planejamento de rotas de entrega de produtos de forma otimizada (buscando o “menor caminho”). Embora, durante a busca de menor caminho, limitam-se ao uso de ruas. Neste contexto emerge o Problema de Roteamento Humano, tal abordagem não se limita a ruas, mas faz uso de todos os caminhos possíveis, por veículos e humanos. Tal problemática, pode ser observada nos planejamentos de rotas em aeroportos, museus e em uma empresa de supply chain que deseja otimizar a rota de entrega dos seus produtos, e aumentar a satisfação dos seus clientes. Tomando como base central, o Problema de Roteamento de Veículos será proposto o Problema de Roteamento Humano. Sua problemática, será demonstrado em um protótipo, capaz de auxiliar no planejamento de rotas humanas e três casos de uso. As ideias do Problema de Roteamento Humano tiveram inspiração no forrageamento dos insetos coletivos