Lot Sizing and Lead Time Quotations in Assembly Systems
Farhad Kianfar, Ghasem Mokhtari
Abstract
Farhad Kianfar, Ghasem Mokhtari
Abstract
Abstract. In this paper, a simultaneous lead time quotation and lot sizing problem in an assembly system is investigated. We address a production system with a product that has deterministic demand over a T-period planning horizon and is produced in lots because of the economy of scale. If a lot is completed before the demand period, inventory carrying cost is incurred. On shortages, a lead time is quoted to customers and a lead time quotation cost is incurred. Finally, if the order is delivered later than its due date period, a tardiness cost is charged. The components supply lead time is stochastic, which follows a discrete distribution. The problem is to decide on the lot size of products and components, supply and production starting periods and the due date of lots (to be quoted to customers) so that relevant costs are minimized. The objective function is the sum of the production, inventory carrying, lead time quotation and tardiness costs. We develop a genetic algorithm to solve the proposed model. An experimental framework is set up to test the eciency of the proposed method, which turns out to rate high, both in terms of cost eectiveness and execution speed.
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Abstract. In this paper, a simultaneous lead time quotation and lot sizing problem in an assembly system is investigated. We address a production system with a product that has deterministic demand over a T-period planning horizon and is produced in lots because of the economy of scale. If a lot is completed before the demand period, inventory carrying cost is incurred. On shortages, a lead time is quoted to customers and a lead time quotation cost is incurred. Finally, if the order is delivered later than its due date period, a tardiness cost is charged. The components supply lead time is stochastic, which follows a discrete distribution. The problem is to decide on the lot size of products and components, supply and production starting periods and the due date of lots (to be quoted to customers) so that relevant costs are minimized. The objective function is the sum of the production, inventory carrying, lead time quotation and tardiness costs. We develop a genetic algorithm to solve the proposed model. An experimental framework is set up to test the eciency of the proposed method, which turns out to rate high, both in terms of cost eectiveness and execution speed.
Key concepts: Lead time, Tardiness, Sizing, Holding cost, Production (economics), Computer science, Time horizon, Build to order