Empirical methods for two-echelon inventory management with service level constraints based on simulation-regression

Fuzzy Logic is used to derive the optimal inventory policies in the Supply Chain (SC) numbers. We examine the performance of the optimal inventory policies by cutting the costs and increasing the supply chain management efficiency. The proposed inventory policy uses multi-agent and Fuzzy logic, and provides managerial insights on the impact of the decision making in all the SC numbers. In particular, we focus on the way in which our agent purchases components using a mixed procurement strategy (combining long and short term planning) and how it sets its prices according to the prevailing market conditions and its own inventory level (because this adaptivity and flexibility are key to its success). In modern global market, one of the most important issues of the supply chain (SC) management is to satisfy changing customer demands and enterprises should enhance the long-term advantage through the optimal inventory control. In this paper an intelligent multi-agent system to simulate supply chain management has been developed.

Single item periodic review inventory control with sales dependent stochastic return flows

This research examines a two-stage supply chain that comprises a supplier who is subject to stochastic disruption and a retailer who has to deal with supply disruption by holding inventory. Under a periodic-review base-stock inventory policy, the main objectives of this study are to determine the optimal inventory policy in the presence of stochastic supply disruption so as to minimise the total inventory cost as well as to analyse the impact of supply disruption on the optimal inventory policy. In this research, the length of a supply disruption is modelled as a continuous random variable, distinguishing it from previous research which modelled the length of a supply disruption as a discrete random variable that receives values only as multiples of the length of a review period. Numerical experiments have been conducted to illustrate the applicability of the proposed inventory model and to examine the effects of various input parameters on the optimal inventory policy. Furthermore, compared with the optimal inventory policy derived when the length of a supply disruption is considered as a multiple of the length of a review period, the proposed inventory model in this research can help derive a more precise optimal inventory policy. [Received: 13 February 2017; Revised: 7 December 2017; Accepted: 17 October 2018]

The existed inventory models hardly consider the impact effect on the price of stock item by the inventory actions of enterprises. On the assumption that the supply of stock item is fixed, the paper analyses the impact effects of inventory actions and gets the optimal dynamic inventory policy under the financial budget. The result of simulations illustrates that the inventory actions of enterprises has certain affections on the price of item. Under the continuous changes of item price and residual inventory bankroll, the optimal inventory policy is a process of dynamic adjustment, and the optimal purchase quantity in every stock period increases by degree.

Contributors

The effect of price fluctuations on optimal inventory control policy can be considerable. Most inventory models assume that purchase prices or production unit costs remain constant over the planning period. Computation of optimal inventory policy, without taking price fluctuations into account, can give results which differ considerably from the optimal inventory policy when price changes are ignored. It is desirable to consider price fluctuations as a parameter in inventory models.

Supply Planning and Inventory Control of Perishable Products Under Lead-Time Uncertainty and Service Level Constraints

Integrated consideration of production planning and maintenance processes is a real world assumption. Specifically, by improving the monitoring equipment such as various sensors or product-embedded information devices in recent years, joint assessment of these processes is inevitable for enhancing the level of the system optimization. By means of this equipment, managers can benefit from a condition-based maintenance (CBM) for monitoring and managing their system. The chief aim of the paper is to develop a stochastic maintenance problem based on CBM activities engaged with a complex applied production problem called flexible job shop scheduling problem (FJSP). This integrated problem considers two maintenance scenarios in terms of corrective maintenance (CM) and preventive maintenance (PM). The activation of scenario is done by monitoring the degradation condition of the system and comparing the associated value by predetermined PM and CM levels. Moreover, to make it more realistic, the developed problem allows breakdown of the system between inspection intervals. The event time and duration of performing the maintenance activities are also considered stochastic. The developed methodology copes with high stochastic complexity of proposed problem through simulation-based optimization (SBO) approach, which works based on harmony search optimization algorithm. The developed items of SBO are discussed on different generated test problems and assessed through statistical methods and new visualization approach. Numerical example shows that the proposed method is practical for proposed integrated CBM and FJSP problem. It also offers a basis for any implementation of CBM on production problems.

Optimal inventory policies for successive generations of a high technology product

Comparing the value of information sharing under different inventory policies in construction supply chain

A “phantom stockout" is a retail stockout phenomenon caused by unobserved inventory shrinkage. Unlike conventional stockouts that can be corrected by inventory replenishment, a phantom stockout persists and requires human inspection. In this study, we formulate such a problem as an infinite‐horizon Bayesian dynamic program with joint inventory inspection and replenishment decisions. This problem is challenging to solve due to non‐convexity and high dimensionality. However, we find that under the Bernoulli shrinkage process, the optimal inventory inspection policy has a simple threshold structure that depends on the number of consecutive zero‐sales periods since the last inspection, while the optimal inventory replenishment policy is the same as the optimal policy without inventory shrinkage. Our numerical studies further demonstrate that this simple and intuitive policy can be an effective heuristic for more general shrinkage processes.

A sustainable inventory model for deteriorating items with power demand and full backlogging under a carbon emission tax

In this paper, an economic production quantity model in a three levels supply chain including multiple non-competing suppliers, single manufacturer and multiple non-competing retailers for multiple products with rework process under integrated and non-integrated structures is developed. In this chain, suppliers ship raw material to the manufacturer and the manufacturer combines the fixed percentage of different kinds of raw material to produce the finished products and then delivers them to the retailers. The Stackelberg game is established among the members of the chain. Optimizing the total profit of the chain under both structures applying the optimal pricing, inventory and production policies is the purpose of the research. Eventually, a numerical example is presented for comparing the total profit of the integrated and non-integrated chains of proposed model and some sensitivity analyses are performed to study the effects of parameter changes on the decision variables and the chain profit.

Optimal control of a dual service rate M/M/1 production-inventory model

Optimal supplier inventory control policies when buyer purchase incidence is driven by past service