Affiliation:
1. Information Systems and Operations Management, Foster Business School University of Washington Seattle Campus Seattle Washington USA
2. School of Business Trinity Western University Langley British Columbia Canada
Abstract
AbstractWe address a production/inventory problem for a single product and machine where demand is Poisson distributed, and the times for unit production and setup are constant. Demand not in stock is lost. We derive a solution for a produce‐up‐to policy that minimizes average cost per unit time, including costs of setup, inventory carrying, and lost sales. The machine is stopped periodically, possibly rendered idle, set up for a fixed period, and then restarted. The average cost function, which we derive explicitly, is quasi‐convex sparately in the produce‐up‐to level Q, the low‐level R that prompts a setup, and jointly in R equals Q. We start by finding the minimizing value of Q where R equals 0, and then extend the search over larger R values. The discrete search may end with R less than Q, or on the matrix diagonal where R equals Q, depending on the problem parameters. Idle time disappears in the cycle when R equals Q, and the two‐parameter system folds into one. This hybrid policy is novel in make‐to‐stock problems with a setup time. The number of arithmetic operations to calculate costs in the (Q,R) matrix depends on a vector search over Q. The computation of the algorithm is bounded by a quadratic function of the minimizing value of Q. The storage requirements and number of cells visited are proportional to it.
Subject
Management of Technology and Innovation,Industrial and Manufacturing Engineering,Management Science and Operations Research