Two-Echelon Inventory Stochastic Model of Supply Chain Based on Service Level Constraints

2014 ◽  
Vol 971-973 ◽  
pp. 2448-2451
Author(s):  
Da Li Jiang ◽  
Guang Fu Zhu ◽  
De Li
Keyword(s):  
Supply Chain ◽  
Stochastic Model ◽  
Service Level ◽  
Inventory Model ◽  
Inventory Level ◽  
Effective Algorithm ◽  
Inventory Cost ◽  
Total Inventory

The study on multi-echelon inventory of supply chain is becoming more and more important in E-business era. This paper proposes a two-echelon inventory model with one supplier and several retailers, in which a certain service level has to be satisfied and the goal is to minimize the total inventory cost. In addtion it puts forward an effective algorithm for this model to obtain the optimal replenishment period and inventory level of each supply chain node.

Comparative multi criteria analysis and dependent optimisation through integrated supply chain

2014 ◽  
Vol 63 (8) ◽  
pp. 1046-1069 ◽  
Author(s):  
Sanjay Sharma ◽  
Akshat Sisodia
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Service Level ◽  
Inventory Level ◽  
Inventory Policies ◽  
Inventory Cost ◽  
Content Type ◽  
Customer Service Level ◽  
Integrated Supply Chain ◽  
Different Levels

Purpose – The purpose of this paper is to compare various inventory policies and their effect on various performance metrics at different levels of a multi stage supply chain. Later the model is integrated to include optimization of entire supply chain through implementation of collaborative supply chain model. Design/methodology/approach – Alternative inventory policies have been developed at different echelons and a comparison reflecting the usability on various factors such as inventory level, inventory cost and service level is presented so as to support the decision-making process. Various inventory policies such as economic order quantity, periodic ordering (T, M) and stock to demand have been considered. Along with the basic assumptions; lead time, demand variability, variability in demand during lead time, stock out costs have also been included to make the model more applicable to practical situations. Findings – After the selection of most appropriate inventory policy at each level through a decision matrix, the total cost of operating such a supply chain is calculated along with other parameters such as service level and inventory turns. The approach is of aggregating the optimized value at each echelon referred to as aggregated supply chain in the paper. Then the concept of integrated supply chain is introduced which optimizes the supply chain as a whole, rather than aggregating local optima. The comparison is made between the two approaches that prove the integrated supply chain's superiority. Furthermore, dependent optimization is run as it is not practically possible for each echelon to optimize at the same time. Originality/value – Each echelon is allowed to optimize at a time and other echelons assume corresponding values. This final comparative multi criterion analysis is based on the three factors, i.e. inventory cost, customer service level and inventory turnover with different weights assigned to each factor at different levels of a supply chain. Finally a consolidation of results is made to reflect the overall preference which proves that an integrated supply chain best serves all the parameters combined together.

Inventory Control and Replenishment of Multi-Product Multi-Echelon Based on Time Cost Under JMI Environment

2013 ◽  
Vol 5 (2) ◽  
pp. 19-30
Author(s):  
Zhi Chen ◽  
Chao Ren ◽  
Ren-long Zhang ◽  
Mi-Yuan Shan
Keyword(s):  
Supply Chain ◽  
Inventory Management ◽  
Service Level ◽  
Control Model ◽  
Management Tool ◽  
Time Cost ◽  
Inventory Cost ◽  
Inventory Costs ◽  
Total Inventory ◽  
Replenishment Strategy

Joint managed inventory is an advanced supply chain inventory management tool, which will effectively tackle the complicated problem between the inventory cost of supply chain and service level. The research on inventory model and its’ control under JMI environment is a hot issue at present. In this paper, the authors deeply discuss the question of the inventory time costs about the multi-product and multi-echelon control model and its’ replenishment strategy under JMI environment. With considering the foundation of JMI and time cost, the authors propose the multi-product multi-echelon inventory cost control model under time cost. Then formulate corresponding replenishment strategy. At last, through a numerical example, the authors discover that the multi-product multi-echelon joint inventory management based on time cost can effectively reduce the total inventory costs and improve the competitiveness of the entire supply chain.

Inventory model in a four-echelon integrated supply chain: modeling and optimization

2017 ◽  
Vol 12 (4) ◽  
pp. 739-762 ◽  
Author(s):  
Abolfazl Gharaei ◽  
Seyed Hamid Reza Pasandideh ◽  
Alireza Arshadi Khamseh
Keyword(s):  
Supply Chain ◽  
Nonlinear Model ◽  
Interior Point ◽  
Inventory Model ◽  
Inventory Cost ◽  
Content Type ◽  
Multi Stage ◽  
Total Inventory ◽  
Integrated Supply Chain ◽  
Stochastic Constraints

Purpose The main purpose is to minimize the total inventory cost of chain, whereas the stochastic constraints are satisfied. In other words, the goal is to find optimum agreed stockpiles and period length for products to minimize the total inventory cost of the chain while the stochastic constraints are fulfilled. Design/methodology/approach This paper designs and optimizes an integrated inventory model in a four-echelon supply chain that contains a supplier, a producer, a wholesaler and multiple retailers. All four levels agree with each other to make an integrated inventory system. Products in this model have a multi-stage production process, and the model is bounded by multiple stochastic constraints. The problem model is nonlinear and large. So, the interior point method as an effective algorithm is used for solving the recent convex nonlinear model. Two numerical examples are solved to demonstrate the application of this methodology and to evaluate the performance of the proposed approach. Findings The findings showed the model is applicable for real-world supply chain problems in the cases that echelons are going to do executive external integration. Also, the Interior Point algorithm has a satisfactory performance and a high efficiency in terms of optimum solution for solving nonlinear and large models. Originality/value The authors designed and optimized the inventory cost in a four-level integrated supply chain in stochastic conditions. The new decision variables, number of chain levels, multi-products, stochastic constraints and multi-stage products in four-level integrated supply chain are other novelties of this paper. The authors provided an efficient algorithm for solving a large-scale and nonlinear model in this research, too.

scholarly journals Pengendalian Persediaan Untuk Mengurangi Biaya Total Persediaan Dengan Pendekatan Metode Periodic Review (R,s,S) Power Approximation Pada Suku Cadang Consumable (Studi Kasus : Job Pertamina Talisman Jambi Merang)

2017 ◽  
Vol 4 (1) ◽  
pp. 8
Author(s):  
Adhi Putra Mahardika ◽  
Muhammad Nashir Ardiansyah ◽  
Efrata Denny S. Yunus
Keyword(s):  
Service Level ◽  
Spare Parts ◽  
Gas Production ◽  
Inventory Level ◽  
Periodic Review ◽  
Inventory Cost ◽  
Turbine Engine ◽  
Total Cost ◽  
Gas Processing ◽  
Power Approximation

Spare parts is one of the production support components which plays an important role for the survival<br />of gas production in the gas processing facility owned by SKN JOB Pertamina Talisman Jambi Merang. The<br />high inventory level increased the high inventory cost for the industry which get the benefit from the efficiency<br />of processes and resources. This research involved consumable spare parts for Solar Turbine engine as much<br />as 25 SKUs with demand character patterned lumpy demand and Poisson distribution. The implementation<br />of policies using Periodic Review (R, s, S) with Power Approximation approach in the inventory system<br />capable to generate a lower total cost inventory by pressing the backorder volume, the booking volume and the<br />inventory levels in a balanced manner. Calculation of Periodic Review (R, s, S) with Power Approximation<br />approach resulted inventory parameter which was able to press the total cost of inventory at 8.54% lower and<br />increase the service level by 1.11%.

scholarly journals Inventory model for deteriorating items with negative exponential demand, probabilistic deterioration and fuzzy lead time under partial back logging

2020 ◽  
Vol 30 (3) ◽  
Author(s):  
Nabendu Sen ◽  
Sumit Saha
Keyword(s):  
Inventory Management ◽  
Lead Time ◽  
Probability Distributions ◽  
Optimal Strategies ◽  
Inventory Model ◽  
Deteriorating Items ◽  
Optimal Time ◽  
Inventory Cost ◽  
Total Inventory ◽  
Negative Exponential

The effect of lead time plays an important role in inventory management. It is also important to study the optimal strategies when the lead time is not precisely known to the decision makers. The aim of this paper is to examine the inventory model for deteriorating items with fuzzy lead time, negative exponential demand, and partially backlogged shortages. This model is unique in its nature due to probabilistic deterioration along with fuzzy lead time. The fuzzy lead time is assumed to be triangular, parabolic, trapezoidal numbers and the graded mean integration representation method is used for the defuzzification purpose. Moreover, three different types of probability distributions, namely uniform, triangular and Beta are used for rate of deterioration to find optimal time and associated total inventory cost. The developed model is validated numerically and values of optimal time and total inventory cost are given in tabular form, corresponding to different probability distribution and fuzzy lead-time. The sensitivity analysis is performed on variation of key parameters to observe its effect on the developed model. Graphical representations are also given in support of derived optimal inventory cost vs. time.

scholarly journals Optimization Of Raw Material Inventory Costs In The Food Supply Chain Using Differential Evolution Algorithm

2018 ◽  
Vol 73 ◽  
pp. 13016
Author(s):  
Mara Huriga Priymasiwi ◽  
Mustafid
Keyword(s):  
Supply Chain ◽  
Differential Evolution ◽  
Food Industry ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Raw Material ◽  
Inventory Cost ◽  
De Algorithm ◽  
Material Requirement ◽  
Total Inventory

The management of raw material inventory is used to overcome the problems occuring especially in the food industry to achieve effectiveness, timeliness, and high service levels which are contrary to the problem of effectiveness and cost efficiency. The inventory control system is built to achieve the optimization of raw material inventory cost in the supply chain in food industry. This research represents Differential Evolution (DE) algorithm as optimization method by minimizing total inventory based on amount of raw material requirement, purchasing cost, saefty stock and reorder time. With the population size, the parameters of mutation control, crossover parameters and the number of iterations respectively 80, 0.8, 0.5, 200. With the amount of safety stock at the company 7213.95 obtained a total inventory cost decrease of 39.95%. Result indicate that the use of DE algorithm help providein efficient amount, time and cost.

A PSO Weighted Estimating the Mean Downstream Demand to Mitigate the Bullwhip Effect in a Supply Chain

2011 ◽  
Vol 383-390 ◽  
pp. 4125-4129
Author(s):  
Ling Tzu Tseng
Keyword(s):  
Particle Swarm Optimization ◽  
Supply Chain ◽  
Particle Swarm ◽  
Bullwhip Effect ◽  
Pso Algorithm ◽  
Inventory Level ◽  
Inventory Cost ◽  
Swarm Optimization ◽  
Demand Information ◽  
Batch Ordering

Bullwhip Effect, Particle Swarm Optimization, Supply Chain, Demand Information Abstract. A deformation phenomenon occurring in business activity, called the bullwhip effect which comes from the demand information is not fully shared among the members of a supply chain, conducts the upstream manufacturer to excessively anticipate the demand capacity of the downstream retailer. The manufacturer improperly decides the amount of the products not only to raise the inventory cost on the way of poorly handling the actually downstream demand, but also to lose the chance of business deals due to its backordering. To cope with the bullwhip effect by taking into account the holding and backorder costs, an evolutionary method based on the Particle Swarm Optimization (PSO) algorithm to estimate the critical parameter, mean downstream demand, is proposed and computer validated in this paper such that the estimated inventory level could be close the really batch ordering of the manufacturer.

scholarly journals Inventory Model with Partial Backordering When Backordered Customers Delay Purchase after Stockout-Restoration

2016 ◽  
Vol 2016 ◽  
pp. 1-16
Author(s):  
Ren-Qian Zhang ◽  
Yan-Liang Wu ◽  
Wei-Guo Fang ◽  
Wen-Hui Zhou
Keyword(s):  
Layer Structure ◽  
Inventory Model ◽  
Inventory Cost ◽  
Cost Component ◽  
Lipschitz Optimization ◽  
Partial Backordering ◽  
Demand Rate ◽  
Holding Cost ◽  
Total Inventory ◽  
Inventory Holding

Many inventory models with partial backordering assume that the backordered demand must be filled instantly after stockout restoration. In practice, however, the backordered customers may successively revisit the store because of the purchase delay behavior, producing a limited backorder demand rate and resulting in an extra inventory holding cost. Hence, in this paper we formulate the inventory model with partial backordering considering the purchase delay of the backordered customers and assuming that the backorder demand rate is proportional to the remaining backordered demand. Particularly, we model the problem by introducing a new inventory cost component of holding the backordered items, which has not been considered in the existing models. We propose an algorithm with a two-layer structure based on Lipschitz Optimization (LO) to minimize the total inventory cost. Numerical experiments show that the proposed algorithm outperforms two benchmarks in both optimality and efficiency. We also observe that the earlier the backordered customer revisits the store, the smaller the inventory cost and the fill rate are, but the longer the order cycle is. In addition, if the backordered customers revisit the store without too much delay, the basic EOQ with partial backordering approximates our model very well.

Sign in / Sign up

Export Citation Format

Share Document