In this paper a simultaneous Lead Time quotation and lot sizing problem in an assembly system is investigated. The researchers 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 and finally if the order is delivered later than its due date period, tardiness cost is charged. The components supply lead time is stochastic which follows a discrete distribution. The problem is to decide on lot sizes of product and components, supply and production starting periods and due date of lots (to be quoted to customers) so that relevant costs are minimized. The objective function is the sum of production, inventory carrying, lead time quotation, and tardiness costs. Then they develop a genetic algorithm to solve the proposed model. Experimental framework is set up to test the efficiency of the proposed method, which turns out to rate high both in terms of cost effectiveness and execution speed.

lot sizing, lead time quotation, genetic algorithms, production planning