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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 ...
Typically, supply-chain managers aim to maximize the profitable operation of their manufacturing and distribution supply chain. This could include measures like maximizing gross margin return on inventory invested (balancing the cost of inventory at all points in the supply chain with availability to the customer), minimizing total operating expenses (transportation, inventory and ...
Economic order quantity (EOQ) – EOQ is a mathematical formula that calculates the optimal order quantity for a particular item based on factors such as demand, lead time, and ordering costs. By using EOQ, businesses can ensure that they are ordering the right amount of inventory to meet demand while minimizing their inventory carrying costs. [9]
In manufacturing, the purpose of scheduling is to keep due dates of customers and then minimize the production time and costs, by telling a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation, utilize maximum resources available and reduce costs.
Material requirements planning (MRP) is a production planning, scheduling, and inventory control system used to manage manufacturing processes. Most MRP systems are software-based, but it is possible to conduct MRP by hand as well. An MRP system is intended to simultaneously meet three objectives:
Ordering cost: This is the cost of placing orders: each order has a fixed cost , and we need to order / times per year. This is K D / Q {\displaystyle KD/Q} Holding cost: the average quantity in stock (between fully replenished and empty) is Q / 2 {\displaystyle Q/2} , so this cost is h Q / 2 {\displaystyle hQ/2}
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