Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (3/4)

Technical report about sustainable urban freight solutions, part 3 of

A structured method for the optimization of the existing last mile logistic flows

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceIn a fast-moving world some business exists due to the interconnectivity between countries. This happens because transports are able to reach the other side of the globe within few days and without being too expensive compensating the lower costs of production and competitive advantages. This is true for well-organized and big supply chains but even them can benefit from integration with disconnected and more complex supply chain as it is the case of e-commerce chains. The transaction of small packages from online shopping required in a totally distinct country of the place of production have very specific characteristics as they are spot flows, hard to predict and to combine with other goods owing to the fact that the destination of flows are different every time and it is not always worth it to dedicate a transport for such a small goods value and in addition most times, logistics have to answer to some challenging marketing requirements meaning they have time windows to fulfil. Last mile is a big part of logistics transports and is one important part of it that can really help companies having better prices and revenues for their transports. Last mile solutions need to be easy to implement and really have to translate in quick gains to logistic companies that are largely reducing their margins to increase competitiveness. In this context, the study aims to investigate and define a method following design Research Methodology hopping to draw some innovative solutions for the problem of last mile. In this respect, the work developed intends to study the solutions already implemented and extract insights on how distribution is made and how to maximize last mile profit through the mature of an algorithm able to reduce inefficiencies in a simple way without having to wiggle too much the structure of businesses as resources of last mile service providers are understood to be scarce as many last mile companies are small sized and running under big logistic players. The solution aims to attain the different marketing requirements exactly as it was defined without having to compromise anything but still being able to make good profit margins and perhaps make room for new opportunities to arise that previously were not profitable

Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (2/4)

Technical report about sustainable urban freight solutions, part 2 of

Development of transportation and supply chain problems with the combination of agent-based simulation and network optimization

Demand drives a different range of supply chain and logistics location decisions, and agent-based modeling (ABM) introduces innovative solutions to address supply chain and logistics problems. This dissertation focuses on an agent-based and network optimization approach to resolve those problems and features three research projects that cover prevalent supply chain management and logistics problems. The first case study evaluates demographic densities in Norway, Finland, and Sweden, and covers how distribution center (DC) locations can be established using a minimizing trip distance approach. Furthermore, traveling time maps are developed for each scenario. In addition, the Nordic area consisting of those three countries is analyzed and five DC location optimization results are presented. The second case study introduces transportation cost modelling in the process of collecting tree logs from several districts and transporting them to the nearest collection point. This research project presents agent-based modelling (ABM) that incorporates comprehensively the key elements of the pick-up and delivery supply chain model and designs the components as autonomous agents communicating with each other. The modelling merges various components such as GIS routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. The entire pick-up and delivery operation are modeled by ABM and modeling outcomes are provided by time series charts such as the number of trucks in use, facilities inventory and travel distance. In addition, various scenarios of simulation based on potential facility locations and truck numbers are evaluated and the optimal facility location and fleet size are identified. In the third case study, an agent-based modeling strategy is used to address the problem of vehicle scheduling and fleet optimization. The solution method is employed to data from a real-world organization, and a set of key performance indicators are created to assess the resolution's effectiveness. The ABM method, contrary to other modeling approaches, is a fully customized method that can incorporate extensively various processes and elements. ABM applying the autonomous agent concept can integrate various components that exist in the complex supply chain and create a similar system to assess the supply chain efficiency.Tuotteiden kysyntä ohjaa erilaisia toimitusketju- ja logistiikkasijaintipäätöksiä, ja agenttipohjainen mallinnusmenetelmä (ABM) tuo innovatiivisia ratkaisuja toimitusketjun ja logistiikan ongelmien ratkaisemiseen. Tämä väitöskirja keskittyy agenttipohjaiseen mallinnusmenetelmään ja verkon optimointiin tällaisten ongelmien ratkaisemiseksi, ja sisältää kolme tapaustutkimusta, jotka voidaan luokitella kuuluvan yleisiin toimitusketjun hallinta- ja logistiikkaongelmiin. Ensimmäinen tapaustutkimus esittelee kuinka käyttämällä väestötiheyksiä Norjassa, Suomessa ja Ruotsissa voidaan määrittää strategioita jakelukeskusten (DC) sijaintiin käyttämällä matkan etäisyyden minimoimista. Kullekin skenaariolle kehitetään matka-aikakartat. Lisäksi analysoidaan näistä kolmesta maasta koostuvaa pohjoismaista aluetta ja esitetään viisi mahdollista sijaintia optimointituloksena. Toinen tapaustutkimus esittelee kuljetuskustannusmallintamisen prosessissa, jossa puutavaraa kerätään useilta alueilta ja kuljetetaan lähimpään keräyspisteeseen. Tämä tutkimusprojekti esittelee agenttipohjaista mallinnusta (ABM), joka yhdistää kattavasti noudon ja toimituksen toimitusketjumallin keskeiset elementit ja suunnittelee komponentit keskenään kommunikoiviksi autonomisiksi agenteiksi. Mallinnuksessa yhdistetään erilaisia komponentteja, kuten GIS-reititys, mahdolliset tilojen sijainnit, satunnaiset puunhakupaikat, kaluston mitoitus, matkan pituus sekä monimuotokuljetukset. ABM:n avulla mallinnetaan noutojen ja toimituksien koko ketju ja tuloksena saadaan aikasarjoja kuvaamaan käytössä olevat kuorma-autot, sekä varastomäärät ja ajetut matkat. Lisäksi arvioidaan erilaisia simuloinnin skenaarioita mahdollisten laitosten sijainnista ja kuorma-autojen lukumäärästä sekä tunnistetaan optimaalinen toimipisteen sijainti ja tarvittava autojen määrä. Kolmannessa tapaustutkimuksessa agenttipohjaista mallinnusstrategiaa käytetään ratkaisemaan ajoneuvojen aikataulujen ja kaluston optimoinnin ongelma. Ratkaisumenetelmää käytetään dataan, joka on peräisin todellisesta organisaatiosta, ja ratkaisun tehokkuuden arvioimiseksi luodaan lukuisia keskeisiä suorituskykyindikaattoreita. ABM-menetelmä, toisin kuin monet muut mallintamismenetelmät, on täysin räätälöitävissä oleva menetelmä, joka voi sisältää laajasti erilaisia prosesseja ja elementtejä. Autonomisia agentteja soveltava ABM voi integroida erilaisia komponentteja, jotka ovat olemassa monimutkaisessa toimitusketjussa ja luoda vastaavan järjestelmän toimitusketjun tehokkuuden arvioimiseksi yksityiskohtaisesti.fi=vertaisarvioitu|en=peerReviewed

Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (1/4)

Technical report about sustainable urban freight solutions, part 1 of

Hybrid Meta-Heuristics for Robust Scheduling

The production and delivery of rapidly perishable goods in distributed supply networks involves a number of tightly coupled decision and optimization problems regarding the just-in-time production scheduling and the routing of the delivery vehicles in order to satisfy strict customer specified time-windows. Besides dealing with the typical combinatorial complexity related to activity assignment and synchronization, effective methods must also provide robust schedules, coping with the stochastic perturbations (typically transportation delays) affecting the distribution process. In this paper, we propose a novel metaheuristic approach for robust scheduling. Our approach integrates mathematical programming, multi-objective evolutionary computation, and problem-specific constructive heuristics. The optimization algorithm returns a set of solutions with different cost and risk tradeoffs, allowing the analyst to adapt the planning depending on the attitude to risk. The effectiveness of the approach is demonstrated by a real-world case concerning the production and distribution of ready-mixed concrete.Meta-Heuristics;Multi-Objective Genetic Optimization;Robust Scheduling;Supply Networks

The Promotion of Intermodal Transport in Central Europe Through the Design and Realisation of eLogistics Services

Die Effizienz des Gütertransports ist ein bedeutender Kernpunkt für die Realisierung von Transportströmen zwischen Herstellern und Kunden. Gegenwärtig wird vorzugsweise der Straßengüterverkehr in ganz Europa eingesetzt, was zu enormen negativen Effekten für die Umwelt und die Einwohner führt. Deswegen müssen neue Methoden und Ansätze für einen nachhaltigen Oberflächentransport berücksichtigt werden, wie sie kontinuierlich von der Politik gefordert und zunehmend durch Unternehmen im europäischen Transportsektor akzeptiert werden. Der intermodale Güterverkehr hat ein entscheidendes Potenzial für eine größere Nachhaltigkeit der Transportprozesse, aber erfordert auch ein größeres Verständnis für die komplexen Zusammenhänge der Prozesse und des Transport-Managements verglichen mit dem monomodalen Verkehr. Die Beherrschung der komplexen und verschiedenen intermodalen Prozesse und Schnittstellen ist der kritischste Faktor bei der Nutzung des intermodalen Verkehrs. Informations- und Kommunikations-Technologien (IKT/ICT), wie IT-Lösungen für strategische Aspekte der Planung von intermodalen Transporten und Promotion der Verkehrsart, können interessierte Transport- und Logistik-Akteure sowie Promotion-Center und Bildungseinrichtungen unterstützen. Der Artikel beschreibt die Anforderungen solcher IT-Lösungen für den intermodalen Güterverkehr unter Berücksichtigung der Komplexität der Transport- Ketten. Der entwickelte »Logistics Chain Generator« wird erläutert und mit anderen IT-Tools verglichen. Abschließend werden Schlussfolgerungen hinsichtlich der weiteren Entwicklung dieses spezifischen IT-Marktsegmentes gezogen.The efficient transport of goods is an important issue for realising cargo flows between industries and customers. Nowadays, primarily road transportation is used across Europe leading to tremendous negative side-effects for the environment and European citizens. Therefore new methods and approaches for sustainable surface transport shall be taken into consideration, as continuously promoted by politics and increasingly accepted by commercial enterprises in the European transport sector. Intermodal transport holds significant potentials for more sustainable transport processes, but requires also a sophisticated understanding of process design and transport management compared with monomodal transport. The handling of complex and divergent intermodal processes and interfaces is the most critical factor for using intermodal transport. Information and Communication Technologies (ICT), such as IT-solutions for strategic aspects of intermodal transport planning and promotion, can help interested transport and logistics users, promotion agencies and educational organisations. The article describes the needs for such ICT-solutions regarding intermodal transport operations and addresses the complexity of the concerned issue. The developed »Logistics Chain Generator« is introduced and compared with other planning tools. Finally, conclusions are drawn for the further development of this specific ICT market segment

A robust solving strategy for the vehicle routing problem with multiple depots and multiple objectives

This document presents the development of a robust solving strategy for the Vehicle Routing Problem with Multiple Depots and Multiple Objectives (MO-MDVRP). The problem tackeled in this work is the problem to minimize the total cost and the load imbalance in vehicle routing plan for distribution of goods. This thesis presents a MILP mathematical model and a solution strategy based on a Hybrid Multi- Objective Scatter Search Algorithm. Several experiments using simulated instances were run proving that the proposed method is quite robust, this is shown in execution times (less than 4 minutes for an instance with 8 depots and 300 customers); also, the proposed method showed good results compared to the results found with the MILP model for small instances (up to 20 clients and 2 depots).MaestríaMagister en Ingeniería Industria

Multi-level evolutionary algorithms resource allocation utilizing model-based systems engineering

This research presents an innovative approach to solve the resource allocation problems using Multi-level Evolutionary Algorithms. Evolutionary Algorithms are used to solve resource allocation problems in different domains and their results are then incorporated into a higher level system solution using another Evolutionary Algorithm to solve base camp planning problems currently faced by the U.S. Department of Defense. Two models are introduced to solve two domain specific models: a logistics model and a power model. The logistic model evaluates routes for logistics vehicles on a daily basis with a goal of reducing fuel usage by delivery trucks. The evaluation includes distance traveled and other constraints such as available resource levels and priority of refilling. The Power model incorporates an open source electrical distribution simulator to evaluate the placement of structures and generators on a map to reduce fuel usage. These models are used as the fitness function for two separate Evolutionary Algorithms to find solutions that reduce fuel consumption within the individual domains. A multi-level Evolutionary Algorithm is then presented, where the two Evolutionary Algorithms share information with a higher level Evolutionary Algorithm that combines the results to account for problem complexity from the interfacing of these systems. The results of using these methods on 5 different base camp sizes show that the techniques provide a considerable reduction of fuel consumption. While the Evolutionary Algorithms show significant improvement over the current methods, the multi-level Evolutionary Algorithm shows better performance than using individual Evolutionary Algorithms, with the results showing a 19.25 % decrease in fuel consumption using the multi-level Evolutionary Algorithm --Abstract, page iii