3,890 research outputs found

    Quantitative Models for Centralised Supply Chain Coordination

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    A Multiple Items EPQ/EOQ Model for a Vendor and Multiple Buyers System Considering Continuous and Discrete Demand Simultaneously

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    This is the author accepted manuscript. The final version is available from IOP Publishing via the DOI in this record.APCOMS-IMEC 2017: joint conference of The 4th Asia Pacific Conference on Manufacturing Systems and The 3rd International Manufacturing Engineering Conference, 7-8 December 2017, Yogyakarta, IndonesiaThis paper proposed a mathematical model for multiple items Economic Production and Order Quantity (EPQ/EOQ) with considering continuous and discrete demand simultaneously in a system consisting of a vendor and multiple buyers. This model is used to investigate the optimal production lot size of the vendor and the number of shipments policy of orders to multiple buyers. The model considers the multiple buyers’ holding cost as well as transportation cost, which minimize the total production and inventory costs of the system. The continuous demand from any other customers can be fulfilled anytime by the vendor while the discrete demand from multiple buyers can be fulfilled by the vendor using the multiple delivery policy with a number of shipments of items in the production cycle time. A mathematical model is developed to illustrate the system based on EPQ and EOQ model. Solution procedures are proposed to solve the model using a Mixed Integer Non Linear Programming (MINLP) and algorithm methods. Then, the numerical example is provided to illustrate the system and results are discussed

    Essays on Shipment Consolidation Scheduling and Decision Making in the Context of Flexible Demand

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    This dissertation contains three essays related to shipment consolidation scheduling and decision making in the presence of flexible demand. The first essay is presented in Section 1. This essay introduces a new mathematical model for shipment consolidation scheduling for a two-echelon supply chain. The problem addresses shipment coordination and consolidation decisions that are made by a manufacturer who provides inventory replenishments to multiple downstream distribution centers. Unlike previous studies, the consolidation activities in this problem are not restricted to specific policies such as aggregation of shipments at regular times or consolidating when a predetermined quantity has accumulated. Rather, we consider the construction of a detailed shipment consolidation schedule over a planning horizon. We develop a mixed-integer quadratic optimization model to identify the shipment consolidation schedule that minimizes total cost. A genetic algorithm is developed to handle large problem instances. The other two essays explore the concept of flexible demand. In Section 2, we introduce a new variant of the vehicle routing problem (VRP): the vehicle routing problem with flexible repeat visits (VRP-FRV). This problem considers a set of customers at certain locations with certain maximum inter-visit time requirements. However, they are flexible in their visit times. The VRP-FRV has several real-world applications. One scenario is that of caretakers who provide service to elderly people at home. Each caretaker is assigned a number of elderly people to visit one or more times per day. Elderly people differ in their requirements and the minimum frequency at which they need to be visited every day. The VRP-FRV can also be imagined as a police patrol routing problem where the customers are various locations in the city that require frequent observations. Such locations could include known high-crime areas, high-profile residences, and/or safe houses. We develop a math model to minimize the total number of vehicles needed to cover the customer demands and determine the optimal customer visit schedules and vehicle routes. A heuristic method is developed to handle large problem instances. In the third study, presented in Section 3, we consider a single-item cyclic coordinated order fulfillment problem with batch supplies and flexible demands. The system in this study consists of multiple suppliers who each deliver a single item to a central node from which multiple demanders are then replenished. Importantly, demand is flexible and is a control action that the decision maker applies to optimize the system. The objective is to minimize total system cost subject to several operational constraints. The decisions include the timing and sizes of batches delivered by the suppliers to the central node and the timing and amounts by which demanders are replenished. We develop an integer programing model, provide several theoretical insights related to the model, and solve the math model for different problem sizes

    Supply Chain

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    Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

    Optimizing replenishment order quantities in uncoordinated supply chains

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    Many modern supply chains can be described as a series of uncoordinated suppliers. That is each supplier establishes their individual inventory and production policies on both the input and output sides. In these supply links there is minimal coordination between suppliers, and typically only prices and delivery guarantees are contracted. As a consequence, the inventory behavior and associated costs do not exhibit standard patterns. This makes it difficult to model and optimize these chains using classical inventory models. The common approach, therefore, for evaluating uncoordinated supply chains is to use Supply Chain Analytics software. These retrieve operational data from Enterprise Resource Planning (ERP) systems and then characterize the historical inventory performance behavior. Nearier (2008) developed a joint production inventory model for estimating inventory costs in uncoordinated chains as an alternative to supply chain analytics. They proposed a (Q, R, δ)2 relationship between each pair of sequential suppliers, where Q is the order quantity, R is the reorder level, and δ is the production or consumption rate. In this arrangement each part has two inventory locations: (i) on the output side of the seller, and (ii) on the input side of the buyer. hi this dissertation, the (Q, R, δ)2 model was extended. Three specific research tasks were accomplished in this regard. First, the inventory estimation accuracy of the original (Q, R, δ)2 model was improved. This was accomplished by deriving a more reliable estimate of the residual inventory at the end of each supply cycle. Further, a more accurate model of the inventory behavior in supply cycles where the seller has no production was developed. A discrete inventory simulation was used to demonstrate a significant improvement in the estimation accuracy, from a 10-30 % error range to within 5% error on average. Second, a prescriptive model for deriving the optimal Q when reducing inventory costs in a (Q, R, δ)2supply relationship was developed. From simulation studies, it was found that due to differences in production batch sizes, production rates, and replenishment order quantities, the inventory cost function exhibits a non-differentiable step-wise convex behavior. Further, the steps are observed to occur at integer ratios of Q and the buyer\u27s production batch. This behavior makes it difficult to analytically derive the optimal Q, which could occur at one of the step points or any intermediate point. A golden section based search heuristic for efficiently deriving the optimal Q was developed. Third, the robustness of Q to demand shifts was studied. A demand shift occurs wherever the mean demand jumps to a higher or lower level, similar to a moving average forecast. The demand shift range beyond, which there is significant deterioration in inventory costs and a change in the supply policy Q is justified, was determined Two supply policies were studied: (i) fixed delivery batch and (ii) fixed production period. For each stochastic demand shift behavior, a delivery batch size or production period that minimizes the total cost of both suppliers is selected

    Three-echelon supply chain delivery policy with trade credit consideration

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    In recent years, collaboration in supply chain approach widely discussed in the literature; but most have dealt with the two-echelon systems. This study focuses on the just-in-time delivery policy of three-echelon supply chain by collaborative approach, where any of the information from the supply chain is available to all the subsystems involved; manufacturer, distribution center and retailer. In the first part of the study a simple model has been developed for a three-echelon supply system that consists of a single manufacturer, a single distribution center and a single retailer. The other part of the study extends this model by considering a upstream integrated delivery supply chain system consisting of a single manufacturer, multiple distribution centers and multiple retailers. In both cases the retailer enjoys a permissible delay in payment. The joint annual cost of the supply chain is obtained by summing the annual relevant costs at all the subsystems. Using the convex property of the cost function, the optimum values of the decision values are initially obtained that minimizes the total cost. Then, these values are adjusted according to feasibility criteria of the credit conditions and other constraints using an algorithm. A numerical example illustrating the solution reveals that total supply chain cost is less by the presented collaborative approach compared to typical delivery policy. A sensitivity analysis also showed the robustness of the new model. This model considers lot-splitting and deferred payment simultaneously. That has not been studied for three-echelon system before. Future extension of this study involves assumption of random demand with cross-transfer delivery, unequal cycle time, shortage consideration, etc

    An operational policy for a single vendor multi buyer integrated inventory supply chain system considering shipping time

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    Since its introduction, the concept of integrated inventory supply chain has received a considerable amount of attention. The majority of studies in the last three decades revealed an increase in holding cost as product moves further down the chain or up the chain. A recent study Hoque (2008) considered vendor’s setup cost and inventory holding cost. Some research also considered fixed transportation cost, which is unrealistic. This study focuses on a single-vendor, multi-buyer scenario and presents three models. First, two models illustrate the transferring of equally-sized batches. Then, a third model considers the transferring of unequally-sized batches in a lot. This study relaxes the assumption that vendor’s holding cost must be greater than or less than all buyer’s holding costs in the system. Also, this research facilitates unequal transportation time and cost for different buyers for greater flexibility. The total system cost is calculated by summing the annual operational cost for all the parties in the system. Optimum values of the decision variables are determined using a direct search method. As presented by the third model, a numerical example demonstrates that the total system cost is less when compared with other two models presented. This study also presents the following: solution procedures to solve each model, many numerical examples to support mathematical findings, and performance comparisons among three findings. In order to justify the lot-splitting approach for solving the integrated inventory problem, alternative models with no lot splitting are devised and tested under the same circumstances. Alternative models with no lot splitting produce similar or better results. Under the same circumstances, the alternate third model is observed to be offering the least total cost for the system. This study also presents a sensitivity analysis to check the robustness of the three models. The future extension of this research may involve considering storage capacity constraint and random demand

    One vendor and multiple retailers system in vendor managed inventory problem with stochastic demand

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    In many supply networks, the retailers are reluctant to share information about demand and inventory level to the vendor. This might lead to many difficulties for the vendor in establishing his own order/production plan. Vendor managed inventory (VMI) policy can help to solve that problem. By applying VMI, information sharing is not really a problem for the vendor anymore and this policy have been proven to help reduce total inventory cost as well as improve customer service level in the supply network. In this research, a VMI model for the system with one vendor and multiple retailers will be developed. The main target of the model is to determine the retailer’s lot size, the vendor’s lot size, the retailer cycle time, and the number of replenishments in a vendor cycle so as to minimise the total system cost. For solution purpose, simulation-optimisation technique using genetic algorithm is employed to help find optimal solutions for the decision variables. Numerical experiments are conducted to show the applicability of the proposed model. Sensitivity analysis is also conducted to examine the effects of some input parameters on the optimal solution

    Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

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    The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment
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