Optimization Models for Solving Lot-Sizing Problems
A Study in Mixed Integer Programming with Feasible Solutions
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In this book, a mixed integer programming (MIP) model formulation has been proposed to find out the optimum order quantity, optimum order time, and the minimum total cost of purchasing, ordering, and holding over the predefined planning horizon. Several forecasting techniques have been used to determine future demands. As in reality the price is not always stable, the prices of the parts were estimated. The companies also need an adequate amount of safety stock on hand to avoid stock-outs due to the uncertainty in demand; therefore, optimal safety stock for each part was calculated based on va...
In this book, a mixed integer programming (MIP) model formulation has been proposed to find out the optimum order quantity, optimum order time, and the minimum total cost of purchasing, ordering, and holding over the predefined planning horizon. Several forecasting techniques have been used to determine future demands. As in reality the price is not always stable, the prices of the parts were estimated. The companies also need an adequate amount of safety stock on hand to avoid stock-outs due to the uncertainty in demand; therefore, optimal safety stock for each part was calculated based on variance in demand, lead time and the target service level. Material requirements planning (MRP) was also done to obtain the economic purchasing schedule of parts. GAMS software was used to validate the model. Accordingly, the model was utilized to find out the optimum solutions of the lot sizing problem using LINGO software.
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