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2015 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Optimization of Integrated Supply Chain Planning under Multiple Uncertainty

verfasst von: Juping Shao, Yanan Sun, Bernd Noche

Verlag: Springer Berlin Heidelberg

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

​The subject of this book is supply chain logistics planning optimization under multiple uncertainties, the key issue in supply chain management. Focusing on the strategic-alliance three-level supply chain, the model of supply chain logistics planning was established in terms of the market prices and the market requirements as random variables of manufactured goods with random expected value programming theory, and the hybrid intelligence algorithm solution model was designed. Aiming at the decentralized control supply chain, in which the nodes were unlimited expansion, the chance-constrained stochastic programming model was created in order to obtain optimal decision-making at a certain confidence level. In addition, the hybrid intelligence algorithm model was designed to solve the problem of supply chain logistics planning with the prices of the raw-materials supply market of the upstream enterprises and the prices of market demand for products of the downstream enterprises as random variables in the supply chain unit. Aimed at the three-stage mixed control supply chain, a logistics planning model was designed using fuzzy random programming theory with customer demand as fuzzy random variables and a hybrid intelligence algorithm solution was created. The research has significance both in theory and practice. Its theoretical significance is that the research can complement and perfect existing supply chain planning in terms of quantification. Its practical significance is that the results will guide companies in supply chain logistics planning in the uncertain environment.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction
Abstract
This is an era of rapid change Courtney (Harvard business review on managing uncertainty. Harvard Business School Press, Boston, 1999). With the background of the rise of knowledge economy and the accelerated pace of economic globalization, the internal and external operating and competition environments of companies are fundamentally changed Croom et al. (Eur J Purch Supply Manag (6):67–83, 2000).
Juping Shao, Yanan Sun, Bernd Noche
Chapter 2. Literature Review
Abstract
As the result of revolution of modern business management mode, the theory and method of supply chain management is also the most important basic theory in the field of management and the frontier of management science. Chopra et al. (Manag Sci 50(1):8–14, 2004 [1]) in Management Science wrote: “Operation and supply chain are currently the most critical themes in management science and improving the theoretical and practical evolution of management science.”
Juping Shao, Yanan Sun, Bernd Noche
Chapter 3. Demand Forecasting Dynamic Equation Model
Abstract
Demand forecasting is the prerequisite and foundation of carrying out the work of supply chain logistics plan. In many cases, demand forecasting is often used by managers to make procurement plans, production plans, transportation plans, and inventory plans, etc. However, the uncertain internal and external factors of the supply chain make prediction results always different from the reality. It means that there is a gap between forecasting and the reality. When the difference between forecast data and actual data is too significant, you will inevitably fail, even if the planning process itself is very close. Therefore, the effectiveness of supply chain is greatly affected by different kinds of forecasting approaches and technology used by supply chain node enterprises.
Juping Shao, Yanan Sun, Bernd Noche
Chapter 4. Optimization of Strategic Alliance Supply Chain Logistics Planning Under Uncertain Environment
Abstract
Very often the market demand and the price of the finished products that the supply chain provides are uncertain. Even for a strategic alliance supply chain which has a dominant core business, what it can coordinate and control is only limited to the supply and demand, price and other related information between node enterprises inside the supply chain. In the face of rapidly changing external market, it is difficult to determine parameters like the quantity of demand and price exactly. But decision makers can derive a probability distribution function of the changing within the market demand and the price of the product through the analysis of the historical data of demand and price. In other words, we can use random variables to describe such uncertain parameters as demand quantity and price.
Juping Shao, Yanan Sun, Bernd Noche
Chapter 5. Optimization of Decentralized Control Supply Chain Logistics Planning Under Uncertain Environment
Abstract
Strategic alliance supply chain can coordinate and control the supply, demand, price and other information of the node enterprises in the supply chain. However, decentralized control supply chain cannot do that. Therefore, for every node enterprise in the decentralized control supply chain, it is hard to accurately acquire the market supply price information of raw materials and market demand price information of finished products. The decision-maker of the enterprises can nevertheless obtain the probability distribution function of the changes of the market prices of raw materials and finished products by analyzing the purchasing prices, sale prices and other historical data. That is to say, two uncertain parameters—market supply price of raw materials and market demand price of finished products can be described by random variables.
Juping Shao, Yanan Sun, Bernd Noche
Chapter 6. Optimization of Mixed Control Supply Chain Logistics Planning Under Uncertain Environment
Abstract
Usually, the demand is described with random variables under uncertain environment. When we describe the demand with variables, we need a great amount of empirical statistics to get the distribution function. However, these data might be hard to get in some cases. The fussy sets theory is then a commonly used and effective method which can quantifiably describe the uncertain demand. The membership function of fuzzy numbers can be determined by the decision makers when using fuzzy numbers to describe the demand, which is much easier to determine the membership function than the determination of distribution functions of random variable.
Juping Shao, Yanan Sun, Bernd Noche
Chapter 7. Conclusion and Future Work
Abstract
Supply chain logistics planning optimization is a kind of planning problem targeting how to reasonably arrange the purchase quantity, production lot size, inventory quantity and transportation quantity of raw materials or finished products of each node enterprise in supply chain under many constraint conditions in order to optimize the operation of supply chain logistics system in the planning period. On the basis of the research customer demand forecasting technique of supply chain and in accordance with the type of management control of the supply chain, this book work over the decision-making model of supply chain logistics planning under uncertain environment, including the three-level strategic-alliance supply chain under environment, decentralized-control supply chain with infinite nodes under environment and three-level mixed control supply chain under environment.
Juping Shao, Yanan Sun, Bernd Noche
Metadaten
Titel
Optimization of Integrated Supply Chain Planning under Multiple Uncertainty
verfasst von
Juping Shao
Yanan Sun
Bernd Noche
Copyright-Jahr
2015
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-662-47250-7
Print ISBN
978-3-662-47249-1
DOI
https://doi.org/10.1007/978-3-662-47250-7