Simulation of different reordering policies for optimizing the inventory of perishable food: an Italian case study

Inventory management represents one of the main criticalities that companies have to face. The challenge is twofold: being able to satisfy a demand whose behavior can significantly vary and be unpredictable in order to avoid stock-out situations, whilst limiting excessive stocks and consequently costs. Some factors can complicate this already inherently difficult task. An example is the presence of constraints on the time for storage, which is the typical case for perishable products such as food and beverages, core business of the Italian company subject of the case study described in this paper. To optimize the reorder process in that context, a simulation model was developed for evaluating the potentials of three traditional reordering policies (i.e., Re-Order Point, Re-Order Interval, and (s, S)) to be applied to a set of products managed by the company, including perishable items, and for testing their performance. The items tested were selected through a preliminary ABC analysis, carried out on the volumes handled. A comparison with the current performance of the company’s and that achievable with the optimized policies is proposed.

Robust tracking control design for fractional-order interval type-2 fuzzy systems

In this paper, a robust control strategy is proposed to deal with the state tracking problem of fractional-order interval type-2 fuzzy system with external disturbance, model uncertainties and state delay. In particular, footprints of uncertainty of the underlying fuzzy system is taken into account to capture and model different level of uncertainties. The uncertainty and disturbance estimator is used to promote the tracking behavior of rejecting disturbance in the control system. First, by applying Lyapunov approach, we focus on the examination of stability and performance of the fractional-order tracking error system. Next, unknown system uncertainties, external disturbances and nonlinearities are accurately estimated via an appropriate filter design. Especially, the proposed control technique does not require any prior knowledge about above said unknown factors and it only require the bandwidth information about low-pass filter.Finally, the feasibility and advantages of the proposed design scheme are confirmed by three numerical examples.

Design of FOPID controller for higher order continuous interval system using improved approximation ensuring stability

This contribution deals with the design of a fractional-order proportional-integral-derivative (FOPID) controller through reduce-order modeling for continuous interval systems. First, a higher order interval plant (HOIP) is considered. The reduced-order interval plant (ROIP) for considered HOIP is derived by multipoint Padé approximation integrated with Routh table. Then, FOPID controller is designed for ROIP to satisfy the phase margin and gain cross over frequency. Thus obtained FOPID controller is implemented on HOIP also to validate the performance of designed FOPID on HOIP. A single-input-single-output (SISO) test system is taken up to elaborate the entire process of controller design. The outcomes affirm the validity of the designed FOPID controller. The designed FOPID controller produced stable results retaining the phase margin and gain cross-over frequency when implemented on HOIP. The results further proved that FOPID controller is working efficiently for ROIP and HOIP.

An economic order interval-based simulation model for perishable products

The aim of this paper is to develop a model for reproducing an Economic Order Interval (EOI)-based inventory control model for perishable products. After a description of the model, a simulation approach is developed and used for determining the optimal parameters of the inventory policy, as well as the relationships between them and the numerical values that can minimize the total inventory management cost, thus making the system as efficient as possible. A numerical example, with realistic data, is proposed for showing the application of the model and its effectiveness for the identification of the optimal inventory policy parameters.