This diploma focuses on the real use of operations research methods in conjunction with logistics technologies. The aim is to show the way of optimization and simulation methods application and to evaluate if these methods are suitable tools for logistics technology application. Following logistic technologies were analysed: Just in Time, Kanban, Cross-Docking and Hub and Spoke. Used mathematical tools include: mixed linear programming models, distribution models, methods of multi-criteria evaluation and simulation models. On the basis of mathematical models 4 examples of new technologies introduction or analysis of already functioning systems have been solved.

The development of air transport industry contributes to the economic growth worldwide. It evolves from a luxury form of transportation to an affordable and quick way to move between places. The airline operation model evolves from a traditional point-to-point operation to a hub-and-spoke model, where airline funnels passenger through a centralized location called hub. This model, while reducing operational cost and increasing connectivity, is also adding more time and distance to one’s journey. The development in aircraft technology however, allows airline to by-pass the traditional hub and fly directly to their destination with a longer-range aircraft with a low capacity, somehow returning to the original operational model of point-to-point flight. However, this new type of aircraft also allows airline to reach a smaller destination that didn’t justify the use of the high-capacity aircraft that was traditionally used on this long-haul flight. Aside from the lower acquisition cost, this smaller aircraft also burns less fuel and reduce the airline financial risk.   The study was focused on locating a new hypothetical hub to connect Europe with Eastern Asia, the top two aviation market by passenger number. This new hub will be strategically located between the two markets, unlike the current Middle-Eastern hub that requires a significant detour. The Buffer Tool that is available in ArcGIS will be utilized to draw a radius between each airport in the study area, where the radius’ values were based on the range of the Airbus A321NEO (New Engine Option). Area with the most intersection will be further analyzed to determine the most reasonable location for the new hub, based on the airport infrastructure and the country’s socio-economic index.   The result of this study shows that the Central Asian region has the most overlapping circle, with the city of Almaty in Kazakhstan emerged as the most potential location for this new hub. The geographical advantage, backed by a relatively strong economy and stable socio-political condition, made Almaty left the other candidates behind.

Yes / Sourcing healthcare practice placements continues to present a challenge for higher education institutions. Equally, the provision of clinical placements by healthcare providers is not at the forefront of their agenda. In view of this, the historic and traditional models of clinical placements is becoming more difficult to provide. In light of this, new models of clinical placements are being explored. Aims: This literature review explores the differing models of clinical placements in use and examines the merits and limitation of each. Methods: A mixed-methods literature review with a pragmatic approach has been used. Findings: Several placement models were described, including the traditional 1:1 model as well as 2:1, 3:1. The hub and spoke, capacity development facilitator, collaborative learning in practice and role emerging placement models were also discussed. Conclusion: There is a considerable paucity of high-quality evidence evaluating differing placement modules. Further research is required to evaluate the differing placement models from a students, clinical educators and service user’s perspective.

Abstract Background: Over the last few years, the principle of cross-docking has prominently spreadthrough the companies in which they try hard to make their supply chain channels efficientand achieve higher demands of the society. Studies claimed that inventory management remains to be challenge for professionals of supply chain as long-term processing times may result in considerable financial losses for firms. Aim: This research aims to evaluate the effectiveness of Hub-and-Spoke cross-dockingstrategy in inventory management by understanding the impact, outcomes or efficacy of its implementation. Methodology: This research has adopted qualitative research method to generate extensive data and deep insights to underlying factors behind organizations' decisions and behavior on the implementation of cross-docking concept. The interviews have been chosen as the main data collection method of this research because it has been used successfully in order to produce rich and detailed information about the participants in the supply chain management.The total sample size of the participants is 10. For instance, the research conducted interviews via In-person, Zoom and WhatsApp video calls. The researcher recruited supply chain managers including companies’ representatives, supply chain practitioners, logistic managers,inventory managers and related stakeholders responsible for executing and overviewing inventory management approaches within their firms operating in Sweden. Thus, individuals can offer useful information related to supply planning, implementing and optimising cross-docking operations within their organisations. Findings and Conclusion: The research has, however, led to the impact of the organizational culture on the sustainable Hub-and-Spoke cross-docking strategy with the participants, all agreeing on the role that culture plays in shaping the structure of the strategy in the long-term. Finally, organizational culture was considered to be the cornerstone system,emphasizing the values of innovation, collaboration, transparency, and employee empowerment that serve as the driving force for its application. Participants highlighted the significance of facilitating discussions on various levels, recognizing the importance of collaborations and teams, establishing training and development systems, creating the culture of continuous improvement, and empowering employees as key measures utilized in dealing with the organizational culture challenges in cross-docking implementation and sustainability. KPIs for the cross-dock's level of success and effectiveness include order fulfillment rates,inventory turnover and customer satisfaction, compliance, employee satisfaction, operational efficiency, and the practice of ethical business conduct and corporate values. Thus, thisresearch proves the connection between the organizational culture and best productivity ,results of cross-docking. This makes it clear that a supportive environment is important for a continued performance in cross-docking operations.

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A less-than-truckload (LTL) carrier typically delivers shipments less than 10,000 pounds (classified as LTL shipment). The size of the shipment in LTL networks provides ample opportunities for consolidation. LTL carriers have focused on hub-and-spoke based consolidation to realize economies of scale. Generally, hub-and-spoke systems work as follows: the shipment is picked up from the shipper and brought to an origin terminal, which is the entry point into the hub-and-spoke system. From the terminal, the freight is sent to the first hub, where it is sorted and consolidated with other shipments, and then sent on to a second hub. It is finally sent from the second hub to the destination terminal, which is the exit point of the hub-and-spoke system. However, the flow of shipments is often more complicated in practice. In an attempt to reduce sorting costs, load planners sometimes take this hub-and-spoke infrastructure and modify it considerably to maximize their truck utilization while satisfying service constraints. Decisions made by a load planner may have a cascading effect on load building throughout the network. As a result, decentralized load planning may result in expensive global solutions. Academic as well as industrial researchers have adapted a hierarchical approach to design the hub-and-spoke networks: generate the hub-and-spoke network, route shipments within this hub-and-spoke network (generate a load plan) and finally, balance the empty trailers. We present mathematical models and heuristics for each of the steps involved in the design of the hub-and-spoke network. The heuristics are implemented in a user-friendly graphical tool that can help understand patterns of freight flow and provide insights into the design of the hub-and-spoke network. We also solved the load planning sub-problem in a parallel computation environment to achieve significant speed-ups. Because of the quick solution times, the tool lays the foundation to address pressing further research questions such as deciding location and number of hubs. We have used data provided by Roadway Parcel Services, Inc. (RPS), now FedEx Ground, as a case-study for the heuristics. Our solutions rival the existing industry solutions which have been a product of expensive commercial software and knowledge acquired by the network designers in the industry.

Transportation is one of the most vital services in modern society. It makes most of the other functions of society possible. Real transportation systems are so large and complex that in order to build the science of transportation systems it will be necessary to work in many areas, such as: Modeling, Optimization and Simulation. We are interested in solutions for the so-called fleet-sizing-and-allocation problem (FSAP). Fleet sizing and allocation problems are one of the most interesting and hard to solve logistic problems. A fleet sizing and allocation problem consists of two interdependent parts. The fleet sizing problem is to determine a number of transportation units that optimally balances service requirements against the cost of purchasing and maintaining the transportation units. The allocation problem is dealing with the repositioning of transportation units to serve future transportation demand. To make the fleet sizing and allocation problem a little bit more tractable we concentrate on logistic systems with a special hub-and-spoke structure. We start with a very simple fleet sizing of one-to-one case. This case will cause us to focus attention on several key issues in fleet sizing. Afterwards, the generalization of the one-to-one system is the one-to-many system. As a simple example can serve the continuous time situation where a single origin delivers items to many destinations. For the case that items are produced in a deterministic production cycle and transportation times are stochastic. We also studied a hub-and-spoke problem with continuous time and stochastic demand. To solve this problem, based on Marginal Analysis, we applied queueing theory methods. The investigation of the fleet-sizing-and-allocation problem for hub-and-spoke systems is started for a single-period, deterministic-demand model. In that the model hub has to decide how to use a given number of TU’s to satisfy a known (deterministic) demand in the spokes. We consider two cases: 1. Renting of additional TU’s from outside the system is not possible, 2. Renting of additional TU’s from outside the system is possible. For each case, based on Marginal Analysis, we developed a simple algorithm, which gives us the cost-minimal allocation. Since the multi-period, deterministic demand problem is NP-hard we suggest to use Genetic Algorithms. Some building elements for these are described. For the most general situation we also suggest to use simulation optimization. To realize the simulation optimization approach we could use the software tool “Calculation Assessment Optimization System” (CAOS). The idea of CAOS is to provide a software system, which separates the optimization process from the optimization problem. To solve an optimization problem the user of CAOS has to build up a model of the system to which the problem is related. Furthermore he has to define the decision parameters and their domain. Finally, we used CAOS for two classes of hub-and-spoke system: 1. A single hub with four spokes, 2. A single hub with fifty spokes. We applied four optimizers – a Genetic Algorithm, Tabu Search, Hybrid Parallel and Hybrid Serial with two distributions (Normal Distribution and Exponential Distribution) for a customer interarrival times and their demand.

Univ., Diss.--Paderborn, 2002.

Hub and Spoke systems, is a important research area in localization theory. This occur, because of these systems are very used in logistics problems, e.g., telecommunication networks and transport of passenger and load.To serve the demand of each pair source destination, basically, the Hub and Spoke system replaces direct connections between the pairs for a hubs network. These hubs group the traffic sharing the transportation medium. To get the best hubs configuration is necessary efficient methods, because this problem, hubs allocation, is a NP-problem. In this work was developed an parallel implementation of the Benders Decomposition method for the uncapacitated multiple allocation hub location problem. In our implementation we use the Skorin- Kapov model. The parallel implementation of Benders Decomposition for hub and spoke problem is not known in literature. The results show that the parallel approach is applicable and more efficient that nonparallel one. The experiments reveals that the parallel algorithm had a time execution 70% minor when compared with the nonparallel one. / Sistemas do tipo eixo raio, tornaram-se uma importante área de pesquisa da teoria de localização nas últimas décadas. Esse destaque deve-se em grande parte ao sucesso de sua utilização em sistemas logísticos, tanto de transporte de passageiros quanto de cargas, e em redes de telecomunicações. Ao invés de servir cada par origem destino de demanda com uma conexão direta, sistemas do tipo eixo raio substituem essas conexões diretas por uma rede de concentradores. Esses concentradores permitem que o tráfego seja agrupado e transportado através de um meio de transporte compartilhado, para ser então entregue aos respectivos destinos. Sendo um problema NP, é necessário o uso de métodos eficientes para sua resolução. Neste trabalho, é desenvolvida uma implementação em paralelo do método de Decomposição de Benders para o problema de localização de concentradores de alocação múltipla não capacitados. A implementação em paralelo do método de Decomposição de Benders para o problema eixo raio não é conhecido na literatura, entretanto os bons resultados obtidos pelo algoritmo paralelo desenvolvido revelam que a abordagem paralela é aplicável e mais eficiente. Nos experimentos realizados, o algoritmo paralelo apresentou um tempo de resposta até 70% menor que o tempo de resposta do algoritmo seqüencial.

As the world changes because of the globalization, the environment of the aviation changes as well. The airlines are forced to adapt to these changes and choose new strategies to operate successfully. The main objective of this thesis is to, according to the title, describe, identify and explain the processes which significantly affect current image of the world of aviation and focus on four Central European legacy carriers. The issues of globalization and its affect on behavior of economic actors, which airlines are, are discussed as first. The following part is dedicated to the characteristics of aviation and its components, the milieu and the behavior of the airlines as well as the newest strategic trends that are being chosen is described as well. The theoretical part is followed by the empirical one where the particular steps of examined airlines are analyzed and explained. The hypotheses concerning the probable behavior and adopted strategies of four analyzed carriers are expressed according to the discovered theoretical principles of the operations of current legacy (network) carriers. Whether the hypotheses are completely or partially confirmed, is discussed at the end of the empirical chapter. Key words: globalization, air transport, legacy carriers, airline alliances, hub and spoke, codeshare