Control policies for single-stage production systems with perishable inventory and customer impatience

• Published in: Annals of operations research Vol. 209; no. 1; pp. 115 - 138
• Main Authors: Ioannidis, Stratos, Jouini, Oualid, Economopoulos, Angelos A., Kouikoglou, Vassilis S.
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.10.2013; Springer Nature B.V
• Subjects: Business and Management; Combinatorics; Costs; Customers; Delay; Inventories; Inventory; Inventory control; Lifetime; Manufacturing execution systems; Operations research; Operations Research/Decision Theory; Optimization; Packaged goods; Perishable goods; Policies; Product life cycle; Random variables; Raw materials; Stockpiling; Studies; Theory of Computation; Perishable inventory; Customer impatience; Admission control; Lead time estimation; Queueing systems; Make-to-stock production
• ISSN: 0254-5330; 1572-9338
• DOI: 10.1007/s10479-012-1058-9

We consider problems of inventory and admission control for make-to-stock production systems with perishable inventory and impatient customers. Customers may balk upon arrival (refuse to place orders) and renege while waiting (withdraw delayed orders) during stockouts. Item lifetimes and customer patience times are random variables with general distributions. Processing, setup, and customer inter-arrival times are however assumed to be exponential random variables. In particular, the paper studies two models. In the first model, the system suspends its production when its stock reaches a safety level and can resume later without incurring any setup delay or cost. In the second model, the system incurs setup delays and setup costs; during stockouts, all arriving customers are informed about anticipated delays and either balk or place their orders but cannot withdraw them later. Using results from the queueing literature, we derive expressions for the system steady-state probabilities and performance measures, such as profit from sales and costs of inventory, setups, and delays in filling customer orders. We use these expressions to find optimal inventory and admission policies, and investigate the impact of product lifetimes and customer patience times on system performance.