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Mixed-integer programming models for supply chain integrated planning

Posted on:2004-01-20Degree:M.A.ScType:Thesis
University:Concordia University (Canada)Candidate:Gupta, Devender MohanFull Text:PDF
GTID:2459390011953749Subject:Engineering
Abstract/Summary:
This thesis is intended to highlight the methodology of integrated planning for coordinating the supply chain in order to improve a system's overall performance. For that, a typical system is considered in which several products must be produced and distributed over several time periods. This work is done on a particular system that includes several suppliers, raw material processing plants, finishing plants and customers. Two main models have been developed based on different approaches, and they have been implemented in two different contexts. Various processes such as raw material procurement, capacity utilization, inventory, and distribution are integrated and optimized. More specifically, the following stages are considered: supply of raw material; production, at raw material processing plants, of product families; production, at finishing plants, of finished goods; and distribution of finished goods to customers. The finished goods are grouped into product families; setups are incurred at the raw material processing plants for product families, and at the finishing plants for individual products. Mixed Integer Program (MIP) formulations are utilized for optimizing the system. Test cases include both small sized and large sized problems. Analysis is done to gain insights into the workings of the models and systems like these in general. In the end, we have successfully demonstrated the utility of managing the supply chain effectively by integrating various processes along with the power and utility of MIP for representing such systems.
Keywords/Search Tags:Supply chain, Integrated, Raw material processing plants, Models
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