Coordination of a Supply Chain with One-Manufacturer and Two-Retailers Under Demand Promotion and Disruption Management Decisions |
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Authors: | Email author" target="_blank">Tiaojun?XiaoEmail author Gang?Yu Zhaohan?Sheng Yusen?Xia |
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Institution: | (1) School of Management Science and Engineering, Nanjing University, Nanjing, Jiangsu, 210093, China;(2) Department of Management Science and Information Systems, McCombs School of Business, The University of Texas at Austin, Austin, Texas 78712-1175, USA;(3) School of Management Science and Engineering, Nanjing University, Nanjing, Jiangsu, 210093, China;(4) Department of Managerial Sciences, Robinson Coll. of Business, Georgia State Univ., Atlanta, GA, 30303 |
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Abstract: | Increasingly, customer service, rapid response to customer requirements, and flexibility to handle uncertainties in both demand
and supply are becoming strategic differentiators in the marketplace. Organizations that want to achieve these benchmarks
require sophisticated approaches to conduct order promising and fulfillment, especially in today’s high-mix low-volume production
environment. Motivated by these challenges, the Available-to-Promise (ATP) function has migrated from a set of availability
records in a Master Production Schedule (MPS) toward an advanced real-time decision support system to enhance decision responsiveness
and quality in Assembly To Order (ATO) or Configuration To Order (CTO) environments. Advanced ATP models and systems must
directly link customer orders with various forms of available resources, including both material and production capacity.
In this paper, we describe a set of enhancements carried out to adapt previously published mixed-integer-programming (MIP)
models to the specific requirements posed by an electronic product supply chain within Toshiba Corporation. This model can
provide individual order delivery quantities and due dates, together with production schedules, for a batch of customer orders
that arrive within a predefined batching interval. The model considers multi-resource availability including manufacturing
orders, production capability and production capacity. In addition, the model also takes into account a variety of realistic
order promising issues such as order splitting, model decomposition and resource expediting and de-expediting. We conclude
this paper with comparison of our model execution results vs. actual historical performance of systems currently in place. |
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Keywords: | supply chain coordination disruption management contract game |
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