Titlebook: Supply Chain Disruption Management; Using Stochastic Mix Tadeusz Sawik Book 2020Latest edition The Editor(s) (if applicable) and The Author

Ergots

Integrated Selection of Supply Portfolio and Scheduling of Production and Distributionistribution in a multi-tier supply chain subject to local and regional disruption risks. Two conflicting problem objectives are minimization of cost and maximization of service level. The three shipping methods are considered for distribution of products: batch shipping with a single shipment of dif

Memorial

A Fair Decision-Making under Disruption Riskscost and customer service level, in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to select suppliers of parts required to complete the orders, allocate the demand for parts among the selected suppliers, and schedule the orders o

身心疲憊

A Robust Decision-Making under Disruption Risksly chain under disruption risks. The robustness refers to an equitably efficient performance of a supply chain in average-case as well as in the worst-case, which reflects the decision makers common requirement to maintain an equally good performance of a supply chain under different conditions. Giv

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Selection of Primary and Recovery Supply Portfolios and Schedulingection of supply portfolios for parts is combined with production scheduling of finished products. Unlike most of reported research on the supply chain risk management which focuses on the risk mitigation decisions taken prior to a disruption, the proposed portfolio approach combines decisions made

Arthritis

Selection of Primary and Recovery Supply and Demand Portfolios and Schedulinguppliers and assembly plants in the presence of supply chain disruption risks. Unlike most of reported research on supply chain disruption management a disruptive event is assumed to impact both a primary supplier of parts and a primary assembly plant of the finished products manufacturer. Then the

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怪物

Tadeusz SawikPresents practical applications of stochastic mixed integer programming for integrated decision-making in supply chain disruption management.Uses computational examples for commercially available soft