Material Requirements Planning: The New Way of Life in Production and Inventory Management
Material Requirements Planning: The New Way of Life in Production and Inventory Management
Quantitative Models for Supply Chain Management
Quantitative Models for Supply Chain Management
Capacity Optimization Planning System (Caps)
Interfaces
Modelling Practical Lot-Sizing Problems as Mixed-Integer Programs
Management Science
bc -- prod: A Specialized Branch-and-Cut System for Lot-Sizing Problems
Management Science
Solving volume and capacity planning problems in semiconductor manufaturing: a computational study
Proceedings of the 40th Conference on Winter Simulation
Heuristic approaches for master planning in semiconductor manufacturing
Computers and Operations Research
Proceedings of the Winter Simulation Conference
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IBM Systems and Technology Group uses operations research models and methods extensively for solving large-scale supply chain optimization (SCO) problems for planning its extended enterprise semiconductor supply chain. The large-scale nature of these problems necessitates the use of computationally efficient solution methods. However, the complexity of the models makes developing robust solution methods a challenge. We developed a mixed-integer programming (MIP) model and supporting heuristics for optimizing IBM's semiconductor supply chain. We designed three heuristics, driven by practical applications, for capturing the discrete aspects of the MIP. We leverage the model structure to overcome computational hurdles resulting from the large-scale problem. IBM uses the model and method daily for operational and strategic planning decisions and has saved substantial costs.