3,470 research outputs found

    Collector Managed Inventory, A Proactive Planning Approach to the Collection of Liquids coming from End-of-life Vehicles

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    In this article we introduce Collector Managed Inventory (CMI) as the reverse logistics counter part of Vendor Managed Inventory (VMI).The collection company takes responsibility for the inventories of cores or materials to be recycled.Experience in forward supply chain management has shown the potential of VMI by bringing the coordination of transportation and inventory decisions to the same supply chain entity.Using information technology called telemetry, we are able to monitor inventory levels at distance.We introduce a proactive planning methodology based on two types of collection orders: must- and can-orders.Every collection period all must-orders have to be collected, while canorders are only collected if they can be combined beneficially with the must-orders.The routing problem is solved by a combination of route generation and set partitioning.The system is illustrated in a real-life case study for Auto Recycling Nederland on the collection of liquids coming from end-oflife vehicles, such as coolant and oil.In several scenarios the old reactive approach is compared to the proactive approach resulting in cost savings up to about 19%.supply;logistics;vehicle routine;distribution;information technology;inventory

    Planning and Scheduling Optimization

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    Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development

    A concise guide to existing and emerging vehicle routing problem variants

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    Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a concise overview of existing and emerging problem variants. Models are typically refined along three lines: considering more relevant objectives and performance metrics, integrating vehicle routing evaluations with other tactical decisions, and capturing fine-grained yet essential aspects of modern supply chains. We organize the main problem attributes within this structured framework. We discuss recent research directions and pinpoint current shortcomings, recent successes, and emerging challenges

    Multiobjective Logistics Optimization for Automated ATM Cash Replenishment Process

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    In the digital transformation era, integrating digital technology into every aspect of banking operations improves process automation, cost efficiency, and service level improvement. Although logistics for ATM cash is a crucial task that impacts operating costs and consumer satisfaction, there has been little effort to enhance it. Specifically, in Vietnam, with a market of more than 20,000 ATMs nationally, research and technological solutions that can resolve this issue remain scarce. In this paper, we generalized the vehicle routing problem for ATM cash replenishment, suggested a mathematical model and then offered a tool to evaluate various situations. When being evaluated on the simulated dataset, our proposed model and method produced encouraging results with the benefits of cutting ATM cash operating costs

    INTELLI 2013, The Second International Conference on Intelligent Systems and Applications

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    The research of optimization techniques in the system of goods distribution from warehouses to final users (vehicle routing problem), made considerable savings on the total cost of transport and, consequently, on the final cost of goods, and produced the models applicable to other operating environments (e.g., transport for disabled people, school, municipal waste collection). The analysis conducted on the different models developed under the VRP highlights the support that these models can give on the infomobility of goods

    The price of payment delay

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    Solving the vehicle routing problem with lunch break arising in the furniture delivery industry

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    In this paper we solve the Vehicle Routing Problem with Lunch Break (VRPLB) which arises when drivers must take pauses during their shift, for example, for lunch breaks. Driver breaks have already been considered in long haul transportation when drivers must rest during their travel, but the underlying optimization problem remains difficult and few contributions can be found for less than truckload and last mile distribution contexts. This problem, which appears in the furniture delivery industry, includes rich features such as time windows and heterogeneous vehicles. In this paper we evaluate the performance of a new mathematical formulation for the VRPLB and of a fast and high performing heuristic. The mixed integer linear programming formulation has the disadvantage of roughly doubling the number of nodes, and thus significantly increasing the size of the distance matrix and the number of variables. Consequently, standard branch-and-bound algorithms are only capable of solving small-sized instances. In order to tackle large instances provided by an industrial partner, we propose a fast multi-start randomized local search heuristic tailored for the VRPLB, which is shown to be very efficient. Through a series of computational experiments, we show that solving the VRPLB without explicitly considering the pauses during the optimization process can lead to a number of infeasibilities. These results demonstrate the importance of integrating drivers pauses in the resolution process
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