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The dynamic lot-size model in inventory theory, is a generalization of the economic order quantity model that takes into account that demand for the product varies over time. The model was introduced by Harvey M. Wagner and Thomson M. Whitin in 1958.
In some literature, [citation needed] the term "economic manufacturing quantity" model (EMQ) is used for "economic production quantity" model (EPQ). Similar to the EOQ model, EPQ is a single product lot scheduling method. A multiproduct extension to these models is called product cycling problem.
The economic lot scheduling problem (ELSP) is a problem in operations management and inventory theory that has been studied by many researchers for more than 50 years. The term was first used in 1958 by professor Jack D. Rogers of Berkeley, [1] who extended the economic order quantity model to the case where there are several products to be produced on the same machine, so that one must decide ...
The Silver–Meal heuristic is a production planning method in manufacturing, composed in 1973 [1] by Edward A. Silver and H.C. Meal. Its purpose is to determine production quantities to meet the requirement of operations at minimum cost. The method is an approximate heuristic for the dynamic lot-size model, perceived as computationally too ...
Economic batch quantity. The economic batch quantity model, or production lot size model is similar to EOQ model in that an optimum number is to be calculated for the batch quantity to be produced. EBq (exabecquerel), a multiple of Becquerel, a unit of radioactivity
If is the cost of setting up a batch, is the annual demand, is the daily rate at which inventory is demanded, is the inventory holding cost per unit per annum, and is the rate of production per annum, the total cost function () is calculated as follows: [13]
A master production schedule may be necessary for organizations to synchronize their operations and become more efficient. An effective MPS ultimately will: Give production, planning, purchasing, and management the information to plan and control manufacturing [3] Tie overall business planning and forecasting to detail operations [3]
Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. [1] DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications [2] [3] [4] Additionally, DEA has been used to assess the performance of natural language ...