Analysis of logistics distribution path optimization planning based on traffic network data

With the development of economy, the distribution problem of logistics becomes more and more complex. Based on the traffic network data, this study analyzed the vehicle routing problem (VRP), designed a dynamic vehicle routing problem with time window (DVRPTW) model, and solved it with genetic algorithm (GA). In order to improve the performance of the algorithm, the genetic operation was improved, and the output solution was further optimized by hill climbing algorithm. The analysis of example showed that the improved GA algorithm had better performance in path optimization planning, the total cost of planning results was 31.44 % less than that of GA algorithm, and the total cost of planning results increased by 11.48 % considering the traffic network data. The experimental results show that the improved GA algorithm has good performance and can significantly reduce the cost of distribution and that research on VRP based on the traffic network data is more in line with the actual situation of logistics distribution, which is conducive to the further application of the improved GA algorithm in VRP

Solving a Closed-Loop Location-Inventory-Routing Problem with Mixed Quality Defects Returns in E-Commerce by Hybrid Ant Colony Optimization Algorithm

This paper presents a closed-loop location-inventory-routing problem model considering both quality defect returns and nondefect returns in e-commerce supply chain system. The objective is to minimize the total cost produced in both forward and reverse logistics networks. We propose a combined optimization algorithm named hybrid ant colony optimization algorithm (HACO) to address this model that is an NP-hard problem. Our experimental results show that the proposed HACO is considerably efficient and effective in solving this model

An Inquiry into Supply Chain Strategy Implications of the Sharing Economy for Last Mile Logistics

As the prevalence of e-commerce and subsequent importance of effective and efficient omnichannel logistics strategies continues to rise, retail firms are exploring the viability of sourcing logistics capabilities from the sharing economy. Questions arise such as, “how can crowdbased logistics solutions such as crowdsourced logistics (CSL), crowdshipping, and pickup point networks (PPN) be leveraged to increase performance?” In this dissertation, empirical and analytical research is conducted that increases understanding of how firms can leverage the sharing economy to increase logistics and supply chain performance. Essay 1 explores crowdsourced logistics (CSL) by employing a stochastic discrete event simulation set in New York City in which a retail firm sources drivers from the crowd to perform same day deliveries under dynamic market conditions. Essay 2 employs a design science paradigm to develop a typology of crowdbased logistics strategies using two qualitative methodologies: web content analysis and Delphi surveys. A service-dominant logic theoretical perspective guides this essay and explains how firms co-create value with the crowd and consumer markets while presenting a generic design for integrating crowdbased models into logistics strategy. In Essay 3, a crowdsourced logistics strategy for home delivery is modeled in an empirically grounded simulation optimization to explore the logistics cost and responsiveness implications of sharing economy solutions on omnichannel fulfillment strategies

Modelling Distribution Routes in City Logistics by Applying Operations Research Methods

The article focuses on the up-to-date subject from the practical as well as scientific point of view. It specifically discusses a proposal of an approach concerning transport or distribution problems in the range of city logistics and investigates possibilities to use opted operations research methods in this particular area. Specific suggestions lie first and foremost in using selected tools of operations research (i.e. a set of methods concerning vehicle routing problem) to model multiple variants of distribution paths from a determined hub to multiple spokes in order to minimise the overall travelled distance in an urban area. As far as the very research goes, to define distribution paths to supply multiple logistics objects in the range of city logistics, ensuing methods are step by step used: Clarke-Wright algorithm, Mayer algorithm and the nearest neighbour algorithm. The article consists of a conceptual section, describing the relevant theory as well as data and methods used, the practical part and the section encompassing an assessment of the key findings, along with the discussion. A suitable combination of adequate operations research methods and their application to city logistics issues is where an innovative solution of this research lies

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

An agent-based approach to customer crowd-shipping

Thesis (MEng)--Stellenbosch University, 2022.ENGLISH SUMMARY: The challenge of effective last-mile deliveries is progressively becoming more important with the acceleration in the e-commerce industry that is accompanied by a growing number of doorstep deliveries. Crowd logistics provides innovative solutions whereby ordinary people become in- volved in the execution of logistics operations. A particular crowd logistics initiative, referred to as customer crowd-shipping, recently gained interest from researchers after initial implemen- tations thereof had been performed by companies such as Walmart and Amazon. The approach involves the use of a retailer’s in-store customers, in addition to regular delivery vehicles, for delivering orders to online customers. Such in-store customers, referred to as occasional drivers, are offered incentives to deliver orders on their way home after visiting the retailer. In this thesis, an agent-based simulation model is proposed for studying the highly dynamic working of the customer crowd-shipping initiative. The model encompasses a traditional last- mile delivery system, complemented by the ability to utilise autonomous occasional drivers. The modelled traditional last-mile delivery system consists of a dedicated fleet of delivery vehicles serving online customers from a single depot. The execution of deliveries is formulated as a vehicle routing problem and subsequently solved by means of well-known vehicle routing heuristics. In addition, the occasional drivers are modelled as autonomous agents who have the ability to act outside of the control of the retailer. Rather than being assigned to particular orders, occasional drivers are presented with potential orders from which they may select an order suitable for them to deliver. Their decision to participate is modelled based on self- interest, where an occasional driver agent aims to maximise the difference between the incentive offered and his or her perceived value of the additional time required to deliver the order. An integrated approach to customer crowd-shipping is developed in order to consider the benefits for both the retailer and occasional drivers. This includes an incentive scheme and a method for identifying online customers as candidates for crowd-shipping. The latter involves the dynamic calculation of the company’s cost to serve an individual customer, which is determined for all online customers. Finally, user-friendly access to the agent-based simulation model is facilitated by a graphical user interface. The proposed model is subjected to systematic verification, ensuring the correct functioning and integration of its subcomponents. Moreover, the model is evaluated under various operating conditions to gain a deeper understanding of the crowd-shipping initiative, while simultaneously validating the model as adequate. In particular, parameter variation, sensitivity analyses, and scenario analyses are conducted, followed by face validation by subject matter experts. The results of the various analyses indicate that customer crowd-shipping may successfully function as an extension to an existing last-mile delivery system, with the potential of reducing both the total delivery cost and customer waiting time. These benefits are, however, shown to be influenced by the incentive scheme and the strategy by which online customers are se- lected as crowd-shipping candidates. Finally, it is deduced that the maturity of the customer crowd-shipping system and the occasional population’s perceived value of time influence the performance of the customer crowd-shipping model.AFRIKAANS OPSOMMING: Die uitdaging van doeltreffende laaste-myl aflewerings word geleidelik belangriker met die versnelling in die e-handelsbedryf wat gepaard gaan met ’n groeiende aantal voorstoepaflewerings. Skare-logistiek bied innoverende oplossings waardeur gewone mense betrokke raak by die uitvoering van logistieke bedrywighede. ’n Sekere skare-logistieke inisiatief, waarna verwys word as kli¨ente-skareversending, het onlangs belangstelling by navorsers ontlok nadat aanvanklike implementering daarvan deur maatskappye soos Walmart en Amazon plaasgevind het. Die benadering behels die gebruik van ’n kleinhandelaar se in-winkel kli¨ente, benewens normale afleweringsvoertuie, om bestellings by aanlynkli¨ente af te lewer. Sulke in-winkel kli¨ente, na wie daar ook verwys word as geleentheidsbestuurders, word aansporings gebied om bestellings op pad huis toe af te lewer nadat hulle die kleinhandelaar besoek het. In hierdie tesis word ’n agent-gebaseerde simulasiemodel voorgestel vir die bestudering van die hoogs-dinamiese werking van die kli¨ente-skareversendingsinisiatief. Die model sluit ’n tradisionele laaste-myl afleweringstelsel in, aangevul deur die mootlikheid om outonome geleentheidsbestuurders te gebruik. Die gemodelleerde tradisionele laaste-myl afleweringstelsel bestaan uit ’n toegewyde vloot afleweringsvoertuie wat aanlynkli¨ente vanaf ’n enkele depot bedien. Die uitvoering van aflewerings word as ’n voertuig-roeteringsprobleem geformuleer en vervolgens deur middel van bekende voertuig-roeteringsheuristieke opgelos. Daarbenewens word die geleentheidsbestuurders as outonome agente gemodelleer wat oor die vermo¨e beskik om buite die beheer van die kleinhandelaar op te tree. Eerder as om aan spesifieke bestellings toegewys te word, word geleentheidsbestuurders potensi¨ele bestellings aangebied waaruit hulle een kan kies wat geskik is om deur hulle afgelewer te word. Hul besluit om deel te neem berus op eiebelang, waar ’n geleentheidsbestuurder-agent poog om die verskil tussen die aansporing wat aangebied word en sy of haar waargenome waarde van die bykomende tyd wat benodig word om die bestelling af te lewer, te maksimeer. ’n Ge¨ıntegreerde benadering tot kli¨ente-skareversending word ontwikkel om die voordele vir beide die kleinhandelaar en geleentheidsbestuurders te oorweeg. Dit sluit ’n aansporingskema in sowel as ’n metode om aanlynkli¨ente as kandidate vir skareversending te identifiseer. Laasgenoemde behels die dinamiese berekening van die maatskappy se koste om ’n individuele kli¨ent te bedien, wat vir alle aanlynkli¨ente bepaal word. Laastens word gebruikersvriendelike toegang tot die agent-gebaseerde simulasiemodel deur ’n grafiese gebruikerskoppelvlak moontlik gemaak. Die voorgestelde model word aan sistematiese verifikasie onderwerp, wat die korrekte funksionering en integrasie van die deelkomponente daarvan verseker. Boonop word die model onder verskeie bedryfstoestande ge¨evalueer om ’n dieper begrip van die kli¨ente-skareversendingsinisiatief te verkry, terwyl die model terselfdertyd as voldoende bekragtig word. In die besonder word parametervariasie, sensitiwiteitsanalises en scenario-ontledings uitgevoer, gevolg deur sigvalidering deur vakkundiges. Die resultate van die verskillende ontledings dui daarop dat kli¨ente-skareversending suksesvol as ’n uitbreiding van ’n bestaande laaste-myl afleweringstelsel kan funksioneer, met die potensiaal om beide die totale afleweringskoste en kli¨entewagtyd te verminder. Daar word egter getoon dat hierdie voordele be¨ınvloed word deur die aansporingskema en die strategie waardeur aanlynkli ¨ente as skareversendingkandidate gekies word. Laastens word afgelei dat die volwassenheid van die kli¨ent-skareversendingstelsel en die bevolking geleentheidsbestuurders se waargenome waarde van tyd die prestasie van die kli¨ente-skareversendingsmodel be¨ınvloed.Master

Poster abstract research showcase College of Science and Technology

Welcome to the College of Science and Technology Research and Innovation Showcase 2014, an event which celebrates the research achievements of our science disciplines. Our research brings together scientists from architecture and the built environment through to computing, engineering, mathematics and physics and biology, geography and environmental science. We are committed to build on our strengths, and our key vision is to drive research growth and impact through exploitation of the synergy between research, innovation and enterprise. This year’s showcase event includes over 70 posters illustrating the excellent research being pursued, a Dean's prize recognising the achievements of an early career researcher, prizes for the best student and best students’ posters and journal papers, and this proceedings of abstracts showing the high quality and range of research in the College of Science and Technology

Three essays on urban freight transport: models and tools for effective city logistics projects

The main purpose of these three years of research, summarized in this thesis, was to investigate the obstacles to the development of the city logistics initiatives by seeking solutions to overcome them through model and framework coming from management and transportation engineering. In particular, following a first analysis of a collection of European projects and a systematic analysis of scientific literature, three main gaps in city logistics have been identified: the lack of the stakeholders’ involvement, the need for data sharing platforms to overcome the current lack of data and the need to define city logistics solutions within the urban ecosystem, making consistent design choices coherently with what is already existing in terms of infrastructures, rules and stakeholders in the context. From these three gaps, three main research questions have arisen: (RQ1) Is it possible to support stakeholders in analysing CL solutions fitting their necessities applying some already existing and consolidate decision-making methods? (RQ2) Is it possible to define a database platform in which it is possible to collect, consult and update as many existing data as possible regarding urban freight transport? (RQ3) How is it possible to optimize city logistics infrastructures in a harmonious and coherent way with respect to the entire city logistics ecosystem? To answers to the research questions, a collection of articles is illustrated in this thesis work. From time to time different methodologies are used and illustrated, derived from the field of management and transport engineering, these different methodologies, such as the Systematic Literature Review, the House of Quality, a framework for building a data sharing platform, the city logistics Ecosystem and a decision-making support model (based on both a covering model and a Monte Carlo simulation) are described in detail in the various chapters of the thesis. In this dissertation work for the first time, the main obstacles to the development of city logistics initiatives, that are the lack of involvement of stakeholders, the lack of data, and the lack of an ecosystem vision of urban transport, have been identified and addressed at the same time. Even if literature sometimes offers some possible solutions to these gaps, few are simple to understand for those who work in the urban freight transport industry, easy to apply and replicable. Both in identifying the gap and in seeking solutions, the solutions showed in this thesis sought to address to those who work in the industry, mainly carriers, retailers, shop owners and public administration representatives, trying to combine scientific research with the search for solutions that can be implemented in practice as requested by such a practical research topic. For this reason, each proposed solution and methodology in this thesis has been implemented and experimented using as a case study the city of Bergamo (and testing its replicability in other European cities such as Saint-Etienne, Luxemburg and Amsterdam). In particular, the initial experience in the “Bergamo Logistica” project, part of the Bergamo 2.035 smart city research program, gave me the opportunity to understand the main critical issues found by the main actors who work in this field (i.e., carriers, couriers, retailers and institutions), to confirm some evidences that I found in the theory (i.e., main research gaps which originates the research questions) and to search for solutions that could both solve research gaps and optimize the daily logistics activities of the operators.The main purpose of these three years of research, summarized in this thesis, was to investigate the obstacles to the development of the city logistics initiatives by seeking solutions to overcome them through model and framework coming from management and transportation engineering. In particular, following a first analysis of a collection of European projects and a systematic analysis of scientific literature, three main gaps in city logistics have been identified: the lack of the stakeholders’ involvement, the need for data sharing platforms to overcome the current lack of data and the need to define city logistics solutions within the urban ecosystem, making consistent design choices coherently with what is already existing in terms of infrastructures, rules and stakeholders in the context. From these three gaps, three main research questions have arisen: (RQ1) Is it possible to support stakeholders in analysing CL solutions fitting their necessities applying some already existing and consolidate decision-making methods? (RQ2) Is it possible to define a database platform in which it is possible to collect, consult and update as many existing data as possible regarding urban freight transport? (RQ3) How is it possible to optimize city logistics infrastructures in a harmonious and coherent way with respect to the entire city logistics ecosystem? To answers to the research questions, a collection of articles is illustrated in this thesis work. From time to time different methodologies are used and illustrated, derived from the field of management and transport engineering, these different methodologies, such as the Systematic Literature Review, the House of Quality, a framework for building a data sharing platform, the city logistics Ecosystem and a decision-making support model (based on both a covering model and a Monte Carlo simulation) are described in detail in the various chapters of the thesis. In this dissertation work for the first time, the main obstacles to the development of city logistics initiatives, that are the lack of involvement of stakeholders, the lack of data, and the lack of an ecosystem vision of urban transport, have been identified and addressed at the same time. Even if literature sometimes offers some possible solutions to these gaps, few are simple to understand for those who work in the urban freight transport industry, easy to apply and replicable. Both in identifying the gap and in seeking solutions, the solutions showed in this thesis sought to address to those who work in the industry, mainly carriers, retailers, shop owners and public administration representatives, trying to combine scientific research with the search for solutions that can be implemented in practice as requested by such a practical research topic. For this reason, each proposed solution and methodology in this thesis has been implemented and experimented using as a case study the city of Bergamo (and testing its replicability in other European cities such as Saint-Etienne, Luxemburg and Amsterdam). In particular, the initial experience in the “Bergamo Logistica” project, part of the Bergamo 2.035 smart city research program, gave me the opportunity to understand the main critical issues found by the main actors who work in this field (i.e., carriers, couriers, retailers and institutions), to confirm some evidences that I found in the theory (i.e., main research gaps which originates the research questions) and to search for solutions that could both solve research gaps and optimize the daily logistics activities of the operators