Abstract
Since the deterioration process can be controlled by freshness-keeping efforts, we study the joint freshness-keeping, ordering, and pricing problems for perishable inventory systems. This problem is modeled as a series of nonlinear programming for different cases, from which the optimal single-period freshness-keeping, ordering, and pricing policies are derived analytically by using the Kuhn-Tucker condition. Then, an algorithm is proposed to implement the policies in real time with little computational efforts. We find a criterion function to evaluate whether it is appropriate to employ freshness-keeping effort. In some scenarios where products deteriorate at a high rate, the freshness-keeping policy depends on the inventory level and has a piecewise structure. When the inventory level is not too high or too low, it is appropriate to employ freshness-keeping effort; otherwise, it is not. The pricing decreases in inventory items, and finally, reach a constant. The order policy has (s, S)-type structure. Based on the solution of the single-period problem, we investigate the stochastic problem over an infinite horizon, where the randomness in both demand and deterioration processes is considered. For the stochastics case, approximately dynamic programming is employed to obtain a joint near-optimal policy. Finally, sensitive analysis for some key parameters is conducted to evaluate their impacts on the joint policy and effectiveness of the algorithm, based on which some insights are revealed for the inventory management of perishable systems.
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More From: IEEE Transactions on Automation Science and Engineering
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