The inventory systems are highly variable and uncertain due to market demand instability, increased environmental impact, and perishability processes. The reduction of waste and minimization of holding and shortage costs are the main topics studied within the inventory management area. The main difficulty is the variability of perishability and other processes that occurred in inventory systems and the solution for a trade-off between sufficient inventory level and waste of products. In this paper, the approach for resolving this trade-off is proposed. The presented approach assumes the application of a state-feedback neural network controller to generate the optimal quantity of orders considering an uncertain deterioration process and the FIFO issuing policy. The development of the control system is based on state-space close loop control along with neural networks. For modelling the perishability process Weibull distribution and FIFO policy are applied. For the optimization of the designed control system, the evolutionary NSGA-II algorithm is used. The robustness of the proposed approach is provided using the minimax decision rule. The worst-case scenario of an uncertain perishability process is considered. For assessing the proposed approach, simulation research is conducted for different variants of controller structure and model parameters. We perform extensive numerical simulations in which the assessment process of obtained solutions is conducted using hyper volume indicator and average absolute deviation between results obtained for the learning and testing set. The results indicate that the proposed approach can significantly improve the performance of the perishable inventory system and provides robustness for the uncertain changes in the perishability process.
This paper describes discrete sliding mode (SM) supply management strategies for inventory systems with perishable goods and transportation losses. In the considered systems, the stock used to satisfy the unknown, bounded and time-varying demand is replenished with some delay from a distant supply source. The on-hand stock deterioration during lead-time delay, as well as commodity losses in supply process are explicitly taken into account. Two supply management strategies are proposed. The first one ensures fast reaction to the imposed demand variations, but may result in excessive control signal magnitude at the beginning of the inventory management process. Therefore, in order to conform to supplier limitations we also develop an alternative control strategy based on the concept of the reaching law. That strategy helps reduce the initial supply rate and satisfy the supplier limitations. A number of desirable properties of both proposed strategies are formulated and formally proved. These properties include full customer demand satisfaction and elimination of the risk of exceeding the warehouse capacity.
In this paper we consider the problem of efficient control of inventory systems with perishable goods. In the analyzed setting the deteriorating stock at a distribution center used to fulfill unknown, time-varying demand is replenished with delay from a supply source. The challenging issue is to achieve the high service level with minimum costs when the replenishment orders are procured with lead-time delay spanning multiple review periods. On the contrary to the typical heuristic approaches, we apply formal methodology based on discrete-time sliding-mode (SM) control. The proposed SM controller with the sliding plane selected for a dead-beat scheme ensures that the maximum service level is obtained in the system with arbitrary delay and any bounded demand pattern. In order to account for the supplier capacity limitations in the systems with input constraints, we also develop an alternative control strategy based on reaching law. Both controllers achieve a given service level with smaller holding costs and reduced order-to-demand variance ratio as compared to the classical order-up-to policy.
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