Product selection, machine time allocation, and scheduling decisions for manufacturing perishable products subject to a deadline

• Published in: Computers & operations research Vol. 35; no. 5; pp. 1671 - 1683
• Main Authors: Cai, X.Q., Chen, J., Xiao, Y.B., Xu, X.L.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.05.2008; Elsevier Science; Pergamon Press Inc
• Subjects: Allocations; Applied sciences; Deadline; Deadlines; Decision making; Decision theory. Utility theory; Exact sciences and technology; Inventory control, production control. Distribution; Machine time allocation; Manufacturers; Operational research and scientific management; Operational research. Management science; Perishable goods; Perishable product; Product selection; Production planning; Production scheduling; Raw materials; Scheduling, sequencing; Stochastic models; Stochastic scheduling; Studies; Machine time allocation; Stochastic scheduling; Production planning; Product selection; Deadline; Perishable product; Stochastic model; Decision making; Flight; Optimal policy; Raw materials; Scheduling; Combinatorial optimization; Modeling; Knapsack problem; Stochastic programming; Production management; Perishable item; Manufacturing process; Production process
• DOI: 10.1016/j.cor.2006.09.027
• ISSN: 0305-0548

We are concerned about the following problem: a manufacturer owns a certain amount of perishable raw material which can be produced into different types of products. He must, however, finish the manufacturing process before a deadline (which represents, e.g., a fixed flight schedule). Due to the deadline constraint and the raw material limit, it is imperative for the manufacturer to determine three decisions: (i) the product types to be produced; (ii) the machine time to be allocated for each product type; and (iii) the sequence to process the products selected. We develop, in this paper, a model to formulate this problem. We show that (i) and (iii) can be determined by analytical rules, and (ii) can be computed by an efficient algorithm. The optimal policy with the three decisions for the problem is therefore completely constructed. We also show the relationships of our model to stochastic scheduling and stochastic knapsack, and discuss the contributions of our work to the two areas.