Numerical methods for stochastic control problems in continuous time
Numerical methods for stochastic control problems in continuous time
Hierarchical decision making in stochastic manufacturing systems
Hierarchical decision making in stochastic manufacturing systems
Simulation with visual SLAM and AweSim
Simulation with visual SLAM and AweSim
Simulation Modeling and Analysis
Simulation Modeling and Analysis
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
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This paper presents the optimal flow control for a one-machine, two-product manufacturing system subject to random failures and repairs. The machine capacity process is assumed to be a finite state Markov chain. The problem is to choose the production rates so as to minimize the expected discounted cost of inventory/backlog over an infinite horizon. We first show that for constant demand rates and exponential failure and repair time distributions of the machine, the hedging point policy is optimal. Next, the hedging point policy is extended to nonexponential failure and repair time distributions models. The structure of the hedging point policy is parameterized by two factors representing the thresholds of involved products. With such a policy, simulation experiments are coupled with experimental design and response surface methodology to estimate the optimal control policy. Our results reveal that the hedging point policy is also applicable to a wide variety of complex problems (i.e. nonexponential failure and repair time distributions) where analytical solutions may not be easily obtained.