This report presents a solution procedure to accomplish efficient routing of vehicles. Specifically, the routing of delivery trucks to transport bulk poultry feed from a single feed mill to various customer farms located in the surrounding region at nearly 50 miles radius was studied. The goal was to minimize the total distance traveled for all routes. The project was divided into two phases. In the first phase, truck delivery records were developed through a system of forms over a period of one week at Purdue, Inc. of Salisbury, Maryland. These records were used for preparation of the data required in the second phase of the project. In the second phase, the 'Sweep' Algorithm by Gillette and Miller was used to generate truck routes on a digital computer. The results obtained through the recommended solution procedure were compared with the routes designed by the dispatcher at Purdue, Inc. These results showed significant savings in total distance traveled over all routes. / Master of Science

This dissertation is submitted in fulfillment of the requirements for the degree of Master of Science, University of the Witwatersrand, Johannesburg, August 2018 / Abstract. The vehicle routing problem is a common combinatorial optimization, which is modelled to determine the best set routes to deploy a fleet of vehicles to customers, in order to deliver or collect goods efficiently. The vehicle routing problem has rich applications in design and management of distribution systems. Many combinatorial optimization algorithms which have been developed, were inspired through the study of vehicle routing problems. Despite the literature on vehicle routing problems, the existing techniques fail to perform well when n (the number of variables defining the problem) is very large, i.e., when n > 50. In this dissertation, we survey exact and inexact methods to solve large problems. Our attention is on the capacitated vehicle routing problem. For exact methods, we investigate only the Cutting Planes method which has recently been used in conjunction with other combinatorial optimization problem algorithms (like the Branch and Bound method) to solve large problems. In this investigation, we study the polyhedral structure of the capacitated vehicle routing problem. We compare two metaheuristics, viz., the Genetic Algorithm and the Ant Colony Optimization. In the genetic algorithm, we study the effect of four different crossover operators. Numerical results are presented and conclusion are drawn, based on our findings. / XL2019

The vehicle routing problem (VRP), is a classic optimization problem that aims to determine the optimal set of routes for a fleet of vehicles to meet the demands of a set of customers. The VRP has been studied for many decades and as such, there are many variants and extensions to the original problem. The research presented here focuses on two different types of vehicle routing and scheduling planning problems: car shipping and fatigue-aware scheduling. In addition to modeling and solving the car shipping problem, this research presents a novel way for ways in which drivers can describe their route preferences in a decision support system. This work also introduces the first fatigue-aware vehicle scheduling problem called the Truck Driver Scheduling Problem with Fatigue Management (TDSPFM). The TDSPFM is utilized to produce schedules that keep the drivers more alert than existing commercial vehicle regulations. Finally, this work analyzes the effect of the starting alertness level on driver alertness for the remainder of the work week and examines a critical shortcoming in existing regulations. / Ph. D.

The global energy requirement is increasing at a rapid pace and fossil fuels have been one of the major players in meeting this growing energy demand. However, the resources for fossil fuels are finite. Therefore, it is essential to develop renewable energy sources like biofuels to help address growing energy needs. A key aspect in the production of biofuel is the biomass logistics chain that constitutes a complex collection of activities, which must be judiciously executed for a cost-effective operation. In this thesis, we introduce a two-phase optimization-simulation approach to determine tactical biomass logistics-related decisions cost effectively in view of the uncertainties encountered in real-life. These decisions include number of trucks to haul biomass from storage locations to a bio-refinery, the number of unloading equipment sets required at storage locations, and the number of satellite storage locations required to serve as collection points for the biomass secured from the fields. Later, an operational-level decision support tool is introduced to aid the "feedstock manager" at the bio-refinery by recommending which satellite storage facilities to unload, how much biomass to ship, how to allocate existing resources (trucks and unloading equipment sets) during each time period, and how to route unloading equipment sets between storage facilities. Another problem studied is the "Bale Collection Problem" associated with the farmgate operation. It is essentially a capacitated vehicle routing problem with unit demand (CVRP-UD), and its solution defines a cost-effective sequence for collecting bales from the field after harvest. / Master of Science

Unternehmen der Transportbranche müssen gerade im operativen Tagesgeschäft bei der Tourenplanung und Transportdisposition Planungsprobleme lösen, die ein hohes Maß an Dynamik aufweisen. Speziell die Inputfaktoren der Tourenplanung sind größtenteils dynamisch und stochastisch. Aus Sicht des Autors kann die Qualität von Tourplanungsergebnissen durch die zeitnahe Berücksichtigung unvorhergesehener Ereignisse nachhaltig verbessert werden. Jedoch findet diese zunehmend erfolgskritische Funktionalität in der Literatur bisher nur unzureichend Beachtung, obwohl das Tourenplanungsproblem (Vehicle Routing Problem (VRP)) eines der wichtigsten und am meisten erforschten kombinatorischen Optimierungsprobleme ist. Verfahren für kapazitierte dynamische Tourenplanungsproblemstellungen sind in der Literatur kaum zu finden. Speziell im Bereich der Algorithmen, die eine große Lösungsgeschwindigkeit, eine leichte Verständlichkeit, eine aus praktischer Sicht akzeptable Lösungsgüte aufweisen und die Möglichkeit besitzen, die aktuellen Routenpläne der Fahrzeuge ausgehend von der momentanen geographischen Position real-time zu verändern, besteht Forschungsbedarf. Die Arbeit geht daher der Forschungsfrage nach, wie ein Verfahren für die dynamische Tourenplanung zu konstruieren ist, welches das kapazitierte dynamische Tourenplanungsproblem mit der Möglichkeit der Änderung des aktuellen Fahrzeugzuges unter Einhaltung sehr kurzer Rechenzeiten bei größtmöglicher Verständlichkeit löst. Durch die genannten Kriterien wird im Rahmen der Arbeit der Schwerpunkt auf die Modifikation von klassischen heuristischen Verfahren für die Lösung von dynamischen Tourenplanungsproblemen gelegt. Die Arbeit befasst sich sowohl mit dem Gesamtkonzept zur Disposition dynamischer Kunden als auch mit konkreten Modellen und Verfahren zur Lösung von Subproblemen innerhalb des Gesamtkonzeptes. Ferner erfolgt die Präsentation von umfangreichen Simulationsergebnissen, die auf der durchgeführten softwaretechnischen Implementierung der entwickelten Verfahren basieren. Die gute Anwendbarkeit der neuen Verfahren in der Praxis wird gezeigt. Zwecks der möglichst ganzheitlichen Betrachtung des Themengebietes erfolgt in der Arbeit zum einen sowohl die Erörterung von quantitativen als auch von qualitativen Aspekten der dynamischen Tourenplanung und zum anderen die Analyse von Schnittstellen zwischen der dynamischen Tourenplanung und eng damit verbundenen Bereichen wie Flottenmanagement oder Auftragseingang bzw. -disposition. Hierzu werden die Informationsflüsse zwischen den beteiligten Elementen im Rahmen des dynamischen Dispositionsprozesses aufgezeigt, telematische Komponenten zur Unterstützung des Informationsmanagements und der Informationsübertragung vorgestellt sowie die benötigten Inputdaten erläutert. Den Schwerpunkt der Arbeit stellt jedoch die Entwicklung von neuen quantitativen Methoden zur dynamischen Tourenplanung dar.

abstract: This thesis presents a successful application of operations research techniques in nonprofit distribution system to improve the distribution efficiency and increase customer service quality. It focuses on truck routing problems faced by St. Mary’s Food Bank Distribution Center. This problem is modeled as a capacitated vehicle routing problem to improve the distribution efficiency and is extended to capacitated vehicle routing problem with time windows to increase customer service quality. Several heuristics are applied to solve these vehicle routing problems and tested in well-known benchmark problems. Algorithms are tested by comparing the results with the plan currently used by St. Mary’s Food Bank Distribution Center. The results suggest heuristics are quite completive: average 17% less trucks and 28.52% less travel time are used in heuristics’ solution. / Dissertation/Thesis / Masters Thesis Industrial Engineering 2015

In this thesis we report several of delivery problems. Here it is mostly describe Vehicle Routing Problem and Split Delivery Problem as suitable methods for the case study of the company Baťa a.s.In this thesis we used one of the most sofisticated software Roadnet Transportation Suite as effective program for distribution and planning routes.Finally we construct analysis as a support to find the optimal solution for the final strategical decision of the company Baťa a.s.

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.

In this study, three different algorithms are implemented to solve thecapacitated vehicle routing problem with and without time windows:ant colony optimization, a genetic algorithm and a genetic algorithmwith self-organizing map. For the capacitated vehicle routing problemthe Augerat et al’s benchmark problems were used and for the capaci-tated vehicle routing problem with time windows the Solomon’sbenchmark problems. All three algorithms were tuned over thirtyinstances per problem with the tuners SPOT and ParamILS. The tuningresults from all instances were combined to the final parameter valuesand tested on a larger set of instances. The test results were used tocompare the algorithms and tuners against each other. The ant colonyoptimization algorithm outperformed the other algorithms on bothproblems when considering all instances. The genetic algorithm withself-organizing map found more best known solutions than any otheralgorithm when using parameters, on the capacitated vehicle routingproblem. The algorithms performed well and several new best knownresults were discovered for the capacitated vehicle routing problem andnew best solutions found by heuristics were discovered for the 100customer Solomon problems. When comparing the tuners they bothworked well and no clear winner emerged.

Syfte: Att undersöka de potentiella fördelarna vid implementering av Lean-baserade metoder för att möta prestanda, tillgänglighet och effektivitet i transportsystemet samt användningen av en varuflödesplan för att identifiera slöseri. Vidare, att observera hur fördelarna med en ruttoptimering kan minimera slöseri och reducera kostnader relaterade till transport samt minskningen av miljöutsläpp, stadsbuller och säkerhet. Metod och genomförande: För att uppnå syftet med denna studie och att besvara forskningsfrågorna har en fallstudie och en litteraturstudie kombinerats och genomförts. Fallstudien innehåller observationer och intervjuer som har genomförts för att samla in information om hur fallföretaget arbetar med transport dagligen, användningen av standardisering och effektivisering samt hantering av ruttplanering. Vidare har en implementering utförts av de föreslagna ruttoptimeringsmetoderna för att få större förståelse för de föreslagna metoderna och litteraturen. Slutligen har en analys och diskussion genomförts där de empiriska resultaten studerats och jämförts med litteraturstudien. Resultat: Genomförandet av Lean-baserade metoder för att identifiera och minska slöseri baserat på prestationsmätningsverktyg, såsom värdeflödekartläggning och användningen av ruttoptimering, har visat flera fördelar. De identifierade fördelarna var kortare körtider för chaufförerna, en minskad total kilometersträcka, en mer optimerad fyllnadsgrad i lastbilarna samt mer effektiv tid vid lastning och lossning av gods. Den sistnämna fördelen påverkar främst tillgängligheten och prestandan av den totala fordon- och chaufförseffektiviteten. En del av fördelarna var tolkbara i monetära termer för att ge insikt om hur de eventuella kostnadsbesparingarna. Rekommendationer: För att få bättre och mer djupgående resultat i framtida studier, föreslås att: fallföretaget kartlägger alla transporter som utförs för att bedöma lönsamheten i vissa körrutter samt för att undersöka hur all transport kan uppdelas geografiskt med hjälp av presenterat material i denna studie; noggrannare observationer av förare under andra veckodagar för att identifiera ytterligare problemområden och förbättringsmöjligheter; standardisera och implementera Lean metoder i närliggande processer i verksamheten för fortsatt strävan efter en lönsam verksamhet, till exempel genom att granska mottagandet av varor från leverantörer och utvärdera möjligheten med att ha lokala leverantörer; slutligen, all personal ska utbilda sig inom Lean och standardiserat arbete för att ytterligare eliminera och minska interna NIT-aktiviteter, såsom väntetid. / Purpose: To explore the possible benefits with the implementation of Lean methods to measure performance, availability and efficiency in transportation, including the use of a value stream map to identify waste. Furthermore, to observe how the benefits with a route optimization eventually can minimize waste and reduce costs related to transportation as well as the reduction of environmental emissions, urban noise and security. Methodology: To achieve the purpose of this study and to solve the research questions, a case study and a literature study has been combined and carried out. The case study contains observations and interviews which has been executed in order to gather information related to how the case-company work with transportation on a daily basis, the usage of standardization and the management of route planning. Moreover, an implementation of the proposed route optimizations has been executed with the purpose of gaining knowledge related to the outcome. Finally, an analysis and discussion has been performed where the empirical results are studied and compared with the literature findings. Findings: The implementation of Lean methods to identify and reduce waste based on performance measuring tools, such as value stream mapping and the use of route optimization, showed several advantages. The identified advantages were shorter driving schedules for the chauffeurs, a reduced overall mile distance, a more optimal degree of filling in the driver trucks and more efficient time spent while loading and unloading the trucks. The last advantage mainly affecting the availability and performance of the overall vehicle efficiency. Some of the advantages were interpretable into monetary terms in order to provide an insight into any cost savings. Recommendations: To gain better and more profound results in any further studies, it is suggested that: the case company map out all transports carried out in order to assess the profitability of certain driving routes, as well as to examine how all transport can be geographically divided using the presented material in this study; more thorough observations of drivers during other weekdays to further identify problem areas and improvement opportunities ought to be done; standardization and implementation of Lean methods in related processes in the company for continued pursuit of profitable operations. For example, by reviewing the receipt of goods from suppliers and reviewing the option of having local suppliers; lastly, all staff gets training and education of Lean methods and standardized work for additional elimination and reduction of internal NIT activities, such as waiting time.