June 29, 2017 - June 29, 2017
3:30 pm – 4:30 pm
T. Ahmadi MSc and T. Schettini MSc
Optimal control policies for an inventory system with commitment lead time
We consider a production firm which faces a Poisson customer demand and uses a base-stock policy to replenish its inventories from an outside source with a fixed lead time. The firm can use a preorder strategy which allows the customers to place their orders before their actual need. The time from a customer’s order until the date a product is actually needed is called the commitment lead time. The firm pays a commitment cost which is increasing in the length of the commitment lead time. For such a system, we prove the optimality of “bang-bang” and “all-or-nothing” policies for the commitment lead time and the base-stock policy, respectively. We study the case where the commitment cost is linear in the length of the commitment lead time in detail. We show that there exists a commitment-cost threshold which dictates the optimality of either a make-to-order or a make-to-stock strategy. The commitment-cost threshold is increasing in the holding-cost and shortage-cost factors and decreasing in the mean lead time demand. For a given base-stock level, we develop a simple and accurate approximation for the corresponding optimal commitment lead time. Finally, we determine the conditions on the commitment-cost factor for the profitability of the make-to-order strategy.
Optimizing the scheduling of a pick and place robotic system
In the last years the packaging industry has registered a steady increase in the demand for robotic systems for pick and place packaging problems. The specific requirements of the pick and place problems can vary, but generally those problems involve at least one input conveyor, from which the system is fed the pieces to be manipulated, and a number of robotic manipulators. In this presentation, we will focus on the problem of computing the scheduling for a pick and place packaging line with two conveyors and with the option of controlling the speed profile of one of the conveyors present in the system. Initially, the problem will be formalized in a Mixed Integer Linear Programming formulation and solved using a Row Generation procedure. Then the problem will be solved using the metaheuristic framework of the Iterated Local Search, where part of the quality of the solutions is foregone in favor of a much faster solution time. Numerical results will be presented, showing the effectiveness of the methods developed.
Location: TU/e, Building 62, Paviljoen F9. Feel free to join, if you are interested!
Eindhoven University of Technology