Papers by Keyword: Supply Chain

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Authors: Hui Hu, Guang Yu Zhu, Jin Sheng Shen
Abstract: The paper concentrates on the issue of coordination and combined optimization of supply chains. All the member has its own interests, so there are conflicts between members motive and overall system objective. In the paper CAS theory is used as standard paradigm and complexity of the supply chain is analyzed. Case study includes some extreme situations of the supply chain in different levels, namely optimization and coordination problem within operation layer, business layer and enterprise layer. From the study, some rules are summarized to study the problem.
Authors: Ling Yun Wei, Ming Xiang Wen, Xiao Guang Zhou
Abstract: This paper aims to compare benefits of Vendor Managed Inventory (VMI) system and Collaborative Planning, Forecasting, and Replenishment (CPFR) system based on (R,Q) inventory strategy. Four-stage supply chain models that are simulated by system dynamics (SD) methods will be used to support the comparison. In addition, factors of total cost for the whole supply chain (TSC) and product fill rate (fr) can assist to evaluate simulation models. The results of this study indicate that benefits and flexibility of CPFR appear to be higher than VMI under (R, Q) strategy, and key parameters have significant impacts on TSC of the two systems.
Authors: Song Yang, Peng Hui Shi, Jian Wei Chi
Abstract: Many traditional forecasting platforms try to make predictions about the future by analyzing patterns that occurred in the past.More sophisticated methods exist, such as exponential smoothing or the Holt-Winters method. Nonetheless, as sophisticated as these methods are, they all suffer from the same deficiency: they only consider the past. While the past is indeed a statistically significant indicator of what will happen in the future, it isnt the only indicator. In multi-echelon supply chain systems, there exists a plethora of highly relevant data that can be tapped into.We have built an Arena model to simulate our manufacturing plants supply chain. As we go forward, we will explain how this model was used to explore the significance of various external data sources such as DC and store inventory levels, open orders, and lead times. Using these findings, we derive a regression-based forecasting algorithm that improves accuracy by 35 percent. More accurate forecasts allow our company to maintain a higher service level, lower safety stock, and a more predictable transportation schedule, all of which lead to significant cost savings.
Authors: Hua Jiang, Zhi Gang Lu
Abstract: An integrated supplier selection problem under fuzzy environment is studied in this paper. Firstly, the linear weight method is used to calculate the scores of suppliers according to their different attributes, such as: quality, service, warranty, delivery, reputation and position, which are assumed as fuzzy variables. Secondly, a fuzzy expected value programming model and a fuzzy chance-constrained programming model are proposed to select the best combination of the suppliers and determine the order quantities. A hybrid intelligent algorithm, based on fuzzy simulation, genetic algorithm and neural network, is used to solve the two models. Finally, a numerical example is given to illustrate the effectiveness of the proposed models.
Authors: Bing Chang Ouyang
Abstract: Considering discrete demand and time-vary unit production cost under a foreseeable time horizon, this study presents an adaptive genetic algorithm to determine the production policy for one manufacturer supplying single item to multiple warehouses in a supply chain environment. Based on Distribution Requirement Planning (DRP) and Just in Time (JIT) delivery policy, we assume each gene in chromosome represents a period. Standard GA operators are used to generate new populations. These populations are evaluated by a fitness function using the total cost of production scheme. An explicit procedure for obtaining the local optimal solution is provided.
Authors: Zhen Wang, Lei Huang
Abstract: Concentrating on the supplier with limited production capacity in supply chain, this paper established a mathematical model for production capacity allocation problem with consideration of multiple regional demands. The genetic algorithm is employed as solution mainframe in which a heuristics rule is developed to initiate the population and an elite pool is adopted to store those solutions with outstanding fitness values. The experimental tests show that the proposed model and algorithm are feasible and effective.
Authors: Chung C. Chang
Abstract: Considering the rapid progress of information technology (IT) and volatility of the marketing environment, the past concept that enterprises run the whole show, has become insufficient in an environment so volatile, challenging and competitive, demonstrating the need of up and downstream supply chain cooperation to survive. Therefore, this research aims at the benefits and related functions of collaborative commerce concepts and knowledge management, constructing a system with the integration and application of collaborative commerce and knowledge management, and then explains the operation of this system through a system prototype, in hopes of proving the practicability of knowledge management and collaborative commerce integration, which will help enterprises gain better competitiveness.
Authors: Li Lin, Lian Fei He
Abstract: This paper analyzed the composition of the multiple agent system, and combine with the characteristics of simulation in multiple agent. This paper proposed a supply chain system structure based on the coordination center, to achieve communications between any two entities through the coordination center. This paper constructed the agent module chart of coordination center, suppliers, producers and distributors, and expounds the function and task flow of the coordination center, and design the mechanism for data transfer between modules, in order to realize the data exchange between different entities. In this model, the coordination center takes effective measures like effectively plan, coordination, dispatch and control for the logistics, cash flow and information flow of supply chain. So it has a good reference value for the practical application of supply chain model.
Authors: Hai Dong, Wei Ling Zhao, Yan Ping Li
Abstract: A novel predictive control strategy is applied to dynamic supply chain management under networked manufacturing. The optimisation-based control scheme aims at a complete management framework for production-inventory systems that is based on model predictive control (MPC) and on a neural network time series forecasting model. The model proves to be very useful in production-inventory systems that is enough to keep production and inventory balance. A move suppression term that penalises the rate of change in the transported quantities through the network increases the system’s robustness. The results show that the proposed scheme can improve significantly the performance of the production-inventory system, due to the fact that more accurate predictions are provided to the formulation of the MPC optimization problem in real time.
Authors: Jian Hua Yang, Kun Niu
Abstract: According to the idea of existing quantity flexibility contract , aiming at the particularity of buyers' market's timeliness product, through introducing buyback contract method, a optimization model of supply chain flexibility contract is put forward which can incent dealer and make up the deficiency of single flexibility contract. An example is given to calculate the contented factors of wholesale price and rebate proportion to take the incentive mechanism effect, and to illustrate that manufacturer and dealer share the risk in the supply chain.
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