398 research outputs found

    Multi-objective Dual-Sale Channel Supply Chain Network Design Based on NSGA-II

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    [[abstract]]In this study, we propose a two-echelon multi-objective dual-sale channel supply chain network (DCSCN) model. The goal is to determine (i) the set of installed DCs, (ii) the set of customers the DC should work with, how much inventory each DC should order and (iv) the distribution routes for physical retailers or online e-tailers (all starting and ending at the same DC). Our model overcomes the drawback by simultaneously tackling location and routing decisions. In addition to the typical costs associated with facility location and the inventory-related costs, we explicitly consider the pivotal routing costs between the DCs and their assigned customers. Therefore, a multiple objectives location-routing model involves two conflicting objectives is initially proposed so as to permit a comprehensive trade-off evaluation. To solve this multiple objectives programming problem, this study integrates genetic algorithms, clustering analysis, Non-dominated Sorting Genetic Algorithm II (NSGA-II). NSGA-II searches for the Pareto set. Several experiments are simulated to demonstrate the possibility and efficacy of the proposed approach.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙

    Automated Warehouse Systems: A Guideline for Future Research

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    This study aims to provide a comprehensive tool for the selection, design, and operation of automated warehouse systems considering multiple automated storage and retrieval system (AS/RS) options as well as different constraints and requirements from various business scenarios. We first model the retrieval task scheduling problem in crane-based 3D AS/RS with shuttle-based depth movement mechanisms. We prove the problem is NP-hard and find an optimality condition to facilitate the development of an efficient heuristic. The heuristic demonstrates an advantage in terms of solving time and solution quality over the genetic algorithms and the other two algorithms taken from literature. Numerical experiments illustrate that when a company tends to have multiple short planning horizons with small task batches (i.e., aims to increase the responsiveness level), adding more shuttles is helpful. However, if a company has a long planning horizon with a large task batch size, having faster cranes is more efficient to reduce the makespan. We then focus on the impacts of the number of shuttles, operational mode, storage policies, and shuttle dispatching rules on the expected cycle time of a tier-to-tier shuttle-based storage and retrieval system. The system is modeled as a discrete-time Markov Chain to derive the shuttle distribution under each scenario create the expected travel time models. Numerical experiments indicate that class-based storage is always better than the random storage policy. The best shuttle dispatching rule under each combination of the number of shuttles, operational mode, and storage policy can be quickly identified through the expected cycle time models which are simple and computation friendly. At last, we study the warehouse design problem considering the choice, design, and operation of 2D AS/RS and 3D AS/RS in a systematic way. The warehouse design problem under consideration aims to reduce the investment while satisfying different business needs measured by the desired throughput capacity. We propose a branch-and-bound algorithm to conquer the computational challenges. With the developed algorithm, an optimal warehouse design can be obtained under different application environments, characterized by the desired throughput capacity, inventory level, and demand rate of each SKU

    New concepts integration on e-learning platforms

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    The learning experience has evolved into the virtual world of the Internet, where learners have the possibility to shift from face-to-face learning environments to virtual learning environments supported by technologies. This concept, called e-learning, emerged in the early 1960s where a group of researchers from the Stanford University, USA began experimenting different ways to publish and assign learning content using a computer. These experiments were the beginning that led to the creation of countless learning platforms, initially constructed in standalone environments and later ported to the Internet as Webbased learning platforms. As initial objectives, these learning platforms include a collection of features to support instructors and learners in the learning process. However, some of these platforms continued to be based on an old instructor-centered learning model and created a collection of outdated technologies that, given the current need to a learner-center learning model and the existence of Web 2.0 technologies, become inadequate. As a solution to address and overcome these challenges, a friendly user interface and a correct root incorporation of Web 2.0 services a platform designed to focus the learning experience and environment personalization into the learner is needed to propose. In an operating system (OS) context the graphic user interface (GUI) is guided by a collection of approaches that details how human beings should interact with computers. These are the key ideas to customize, install, and organize virtual desktops. The combination of desktop concepts into a learning platform can be an asset to reduce the learning curve necessary to know how to use the system and also to create a group of flexible learning services. However, due to limitations in hypertext transfer protocol-hypertext markup language (HTTP-HTML) traditional solutions, to shift traditional technologies to a collection of rich Internet application (RIA) technologies and personal learning environments (PLEs) concepts is needed, in order to construct a desktop-like learning platform. RIA technologies will allow the design of powerful Web solutions containing many of the characteristics of desktop-like applications. Additionally, personal learning environments (PLEs) will help learners to manage learning contents. In this dissertation the personal learning environment box (PLEBOX) is presented. The PLEBOX platform is a customizable, desktop-like platform similar to the available operating systems, based on personal learning environments concepts and rich Internet applications technologies that provide a better learning environment for users. PLEBOX developers have a set of tools that allow the creation of learning and management modules that can be installed on the platform. These tools are management learning components and interfaces built as APIs, services, and objects of the software development kit (SDK). A group of prototype modules were build for evaluation of learning and management services, APIs, and SDKs. Furthermore, three case studies were created in order to evaluate and demonstrate the learning service usage in external environments. The PLEBOX deployment and corresponding features confirms that this platform can be seen as a very promising e-learning platform. Exhaustive experiments were driven with success and it is ready for use.A experiência de aprendizagem baseada em tecnologias evoluiu para o mundo virtual da Internet, onde os alunos têm a possibilidade de mudar uma aprendizagem presencial em sala de aula para uma aprendizagem baseada em ambientes virtuais de aprendizagem suportados por tecnologias. O conceito de e-learning surgiu nos anos sessenta (1960) quando um grupo de investigadores da Universidade de Standford, nos Estados Unidos, começaram a experimentar diferentes formas de publicar e atribuir conteúdos de aprendizagem através do computador. Estas experiências marcaram o começo que levou à criação de inúmeras plataformas de aprendizagem, inicialmente construídas em ambientes isolados e depois migradas para a Internet como plataformas de aprendizagem baseadas na Web. Como objectivos inicias, estas plataformas de aprendizagem incluem um conjunto de recursos para apoiar professores e alunos no processo de aprendizagem. No entanto, algumas destas plataformas continuam a ser baseadas em velhos modelos de aprendizagem centrados no professor, criadas com base em tecnologias ultrapassadas que, dadas as necessidades actuais de um modelo de aprendizagem centrado no aluno e da existência de tecnologias baseadas na Web 2.0, se tornaram inadequadas. Como abordagem para enfrentar e superar estes desafios propõem-se uma plataforma focada na personalização do ambiente de aprendizagem do aluno, composta por uma interface amigável e uma correcta incorporação de raiz de serviços da Web 2.0. No contexto dos sistemas operativos (SOs) o graphic user interface (GUI) é desenhado tendo em conta um conjunto de abordagens que detalha como as pessoas devem interagir com os computadores. Estas são as ideias chave para personalizar, instalar e organizar áreas de trabalho virtuais. A combinação do conceito desktop com uma plataforma de aprendizagem pode ser um trunfo para reduzir a curva de aprendizagem necessária para saber como utilizar o sistema e também para criar um grupo de serviços flexíveis de aprendizagem. No entanto, devido as limitações em soluções tradicionais hypertext transfer protocol - hypertext markup language (HTTP - HTML), é necessário migrar estas tecnologias para um grupo de tecnologias rich Internet application (RIA) e conceitos presentes em ambientes personalizados de aprendizagem (personal learning environment - PLE) para construir uma plataforma baseada em ambientes de trabalho virtuais de aprendizagem. As tecnologias RIA irão permitir a criação de soluções Web poderosas que contêm muitas das características disponíveis em aplicações desktop. Adicionalmente, o conceitos de PLE irá ajudar os alunos a gerir os seus próprios conteúdos de aprendizagem. Nesta dissertação, com base nas características apresentadas anteriormente, é apresentada a personal learning environment box (PLEBOX). A plataforma PLEBOX é uma solução de aprendizagem parametrizável com um ambiente de trabalho semelhante aos sistemas operativos actuais, baseando-se em personal learning environments e tecnologias RIA que fornecem um melhor ambiente de aprendizagem para os seus utilizadores. Os programadores da PLEBOX têm ao seu dispor um conjunto de ferramentas que permitem a criação de módulos de aprendizagem e administração que podem ser instalados na plataforma. Estas ferramentas são componentes de aprendizagem e interfaces construídos como APIs, serviços e objectos do software development kit (SDK). Foi construído um conjunto de módulos com o objectivo de avaliar e demonstrar os serviços de aprendizagem, os serviços de gestão, APIs e SDKs. Para além disso, foram criados três casos de estudo para avaliar e demonstrar a utilização dos serviços de aprendizagem em ambientes externos. O desenvolvimento efectuado até ao momento na PLEBOX e respectivos recursos confirma que esta plataforma pode ser vista com uma promissora plataforma de aprendizagem (e-learning), totalmente modular e adaptativa. Realizaram-se experiências exaustivas para testar a plataforma e estas foram realizadas com sucesso num ambiente real, estando assim a plataforma pronta para exploração real

    Design and Development of Smart Brain-Machine-Brain Interface (SBMIBI) for Deep Brain Stimulation and Other Biomedical Applications

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    Machine collaboration with the biological body/brain by sending electrical information back and forth is one of the leading research areas in neuro-engineering during the twenty-first century. Hence, Brain-Machine-Brain Interface (BMBI) is a powerful tool for achieving such machine-brain/body collaboration. BMBI generally is a smart device (usually invasive) that can record, store, and analyze neural activities, and generate corresponding responses in the form of electrical pulses to stimulate specific brain regions. The Smart Brain-Machine-Brain-Interface (SBMBI) is a step forward with compared to the traditional BMBI by including smart functions, such as in-electrode local computing capabilities, and availability of cloud connectivity in the system to take the advantage of powerful cloud computation in decision making. In this dissertation work, we designed and developed an innovative form of Smart Brain-Machine-Brain Interface (SBMBI) and studied its feasibility in different biomedical applications. With respect to power management, the SBMBI is a semi-passive platform. The communication module is fully passive—powered by RF harvested energy; whereas, the signal processing core is battery-assisted. The efficiency of the implemented RF energy harvester was measured to be 0.005%. One of potential applications of SBMBI is to configure a Smart Deep-Brain-Stimulator (SDBS) based on the general SBMBI platform. The SDBS consists of brain-implantable smart electrodes and a wireless-connected external controller. The SDBS electrodes operate as completely autonomous electronic implants that are capable of sensing and recording neural activities in real time, performing local processing, and generating arbitrary waveforms for neuro-stimulation. A bidirectional, secure, fully-passive wireless communication backbone was designed and integrated into this smart electrode to maintain contact between the smart electrodes and the controller. The standard EPC-Global protocol has been modified and adopted as the communication protocol in this design. The proposed SDBS, by using a SBMBI platform, was demonstrated and tested through a hardware prototype. Additionally the SBMBI was employed to develop a low-power wireless ECG data acquisition device. This device captures cardiac pulses through a non-invasive magnetic resonance electrode, processes the signal and sends it to the backend computer through the SBMBI interface. Analysis was performed to verify the integrity of received ECG data

    Normalizing and Procurement optimization with Supermarket and Asset monitoring

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    Automobile part suppliers have struggled hard in the past to meet the requirements of the manufacturing companies. The Original Equipment Manufacturers (OEM) are constantly facing demand changes from the customer end. The connected world has raised the expectation of customers to provide cost efficient yet quality automobiles. Part suppliers are stressed to deliver the products in Just-In-Time (JIT) sequence to reduce the bulk stock in the warehouses. The thesis revolves around the review of JIT models in the automobile assembly process. It specially focuses on the importance of supermarket and their uses in providing the parts through tow train scheduling and routing. The models which are already existing are revised by changing certain criteria and combining all the models published into one system to make it easy for the readers to understand. The purpose of the model normalization is to have visibility on quantity of parts needed in supermarket. This is achieved by the normalized routing and scheduling models which exactly tells when, where and the number of parts transported to the desired work floor at specific time just before assembling. This gives the number of parts being used from the supermarket. From this the number of parts needed on the supermarket and subsequently to the warehouse are calculated. The second half of the thesis focuses on procurement optimization after the revised demand of inventory in the warehouse. Procurement optimization paves way for choosing the right supplier according to the volatility in demand. The second half of the thesis discusses about the advantages of super market installation on supplier selection by doing procurement optimization using Mixed Integer Linear Programing. To end the re-search work on the automobile assembly process, the current problems faced by the industry and especially by the suppliers are discussed. A new way to mitigate the supplier loss is discussed with the introduction of Internet of Things (IoT) based solutions by tracking the assets. Asset monitoring devices have been gaining attention worldwide to safely transport the goods without damage. Transparency and visibility is provided in the form of bidirectional gateway process by the wireless asset monitoring devices. Not only the suppliers but also the OEMs are benefitted as it supports the JIT process and faster assembly of the automobiles with less number of damages
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