Spare Parts Inventory Management with Substitution-Dependent Reliability
نویسندگان
چکیده
Motivated to apply sustainable supply chain principles to air-pollution control systems, this paper presents a dynamic inventory-management approach where substitution is possible to maintain these systems’ equipment. An air-pollution control system’s subsequent reliability depends on the replacement equipment selected. The corresponding problem is formulated as a stochastic dynamic program. Because the state and action space are prohibitively large, the approximate policy iteration algorithm is adapted to generate highquality solutions. Therefore, this work replaces the value function with an affine combination of nonlinear basis functions and shows that a relaxation of the policy improvement step requires the solving of a mixed integer linear program. This approach helps in the designing of an algorithm that improves the quality of the approximation by solving a convex optimization problem. To assess the quality of resulting solutions, a lower bound is developed by considering a relaxation of the problem. In addition, two classes of heuristics are proposed based on a rolling horizon two-stage stochastic programming formulation of the problem and a standard base-stock ordering policy. The performance of proposed policies is tested on a variety of settings, and results show that the approximate dynamic programming (ADP) policies are near-optimal in the settings of interest and significantly outperform available benchmarks. The following analysis reveals that the proposed inventory replenishment policies resemble a base-stock policy with occasional deviations, and assignment and substitution decisions are determined by balancing the reliability with ordering, holding, and shortage costs.
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