scholarly journals Optimal Cycle Service Level for Continuous Stocked Items with Limited Storage Capacity

2018 ◽  
Vol 4 (2) ◽  
pp. 82
Author(s):  
Kanokwan Singha ◽  
Jirachai Buddhakulsomsiri ◽  
Parthana Parthanadee
Keyword(s):  
Inventory Management ◽  
Service Level ◽  
Storage Space ◽  
Continuous Review ◽  
Holding Cost ◽  
Total Inventory ◽  
Review Cycle ◽  
Capacity Cost ◽  
Inventory Holding ◽  
Space Capacity

This paper involves determining an optimal cycle service level for continuously stocked items that explicitly considers storage space capacity. Inventory management is under a continuous review policy. The total inventory management cost consisting of ordering cost, inventory holding cost, shortage cost, and over-capacity cost. Shortage items are assumed to be backlogged. A numerical example is provided to demonstrate the method. Keywords: Continuous Review; Cycle Service Level; Storage Space Capacity; Over-Capacity Cost

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.

A MULTI-PERIOD INVENTORY MODEL FOR DETERIORATING ITEMS IN UNCERTAIN ENVIRONMENT

2013 ◽  
Vol 21 (supp01) ◽  
pp. 113-125 ◽  
Author(s):  
YUFU NING ◽  
LIMEI YAN ◽  
HUANBIN SHA
Keyword(s):  
Equivalent Form ◽  
Service Level ◽  
Deteriorating Items ◽  
Inventory Problem ◽  
Total Cost ◽  
Uncertain Variables ◽  
Holding Cost ◽  
Inventory Holding Cost ◽  
Expected Total Cost ◽  
Inventory Holding

A model is constructed for a type of multi-period inventory problem with deteriorating items, in which demands are assumed to be uncertain variables. The objective is to minimize the expected total cost including the ordering cost, inventory holding cost and deteriorating cost under constraints that demands should be satisfied with some service level in each period. To solve the model, two methods are proposed in different cases. When uncertain variables are linear, a crisp equivalent form of the model is provided. For the general cases, a hybrid algorithm integrating the 99-method and genetic algorithm is designed. Two examples are given to illustrate the effectiveness of the model and solving methods.

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.

scholarly journals Modeling and Optimization of Stochastic Joint Replenishment and Delivery Scheduling Problem with Uncertain Costs

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Lin Wang ◽  
Hui Qu ◽  
Yanhui Li ◽  
Jing He
Keyword(s):  
Inventory Management ◽  
Differential Evolution Algorithm ◽  
Joint Replenishment ◽  
Total Cost ◽  
Operational Conditions ◽  
Long Run ◽  
Holding Cost ◽  
Fuzzy Inventory ◽  
Inventory Holding ◽  
Delivery Scheduling

The stochastic joint replenishment and delivery scheduling (JRD) problem is a key issue in supply chain management and is a major concern for companies. So far, all of the work on stochastic JRDs is under explicit environment. However, the decision makers often have to face vague operational conditions. We develop a practical JRD model with stochastic demand under fuzzy backlogging cost, fuzzy minor ordering cost, and fuzzy inventory holding cost. The problem is to determine procedures for inventory management and vehicle routing simultaneously so that the warehouse may satisfy demand at a minimum long-run average cost. Subsequently, the fuzzy total cost is defuzzified by the graded mean integration representation and centroid approaches to rank fuzzy numbers. To find optimal coordinated decisions, a modified adaptive differential evolution algorithm (MADE) is utilized to find the minimum long-run average total cost. Results of numerical examples indicate that the proposed JRD model can be used to simulate fuzzy environment efficiently, and the MADE outperforms genetic algorithm with a lower total cost and higher convergence rate. The proposed methods can be applied to many industries and can help obtaining optimal decisions under uncertain environment.

Study on the (s, S) Policy for the Manufacturing Enterprises Inventory Management

2014 ◽  
Vol 926-930 ◽  
pp. 3978-3983
Author(s):  
Jian Yang ◽  
Can Rong Zhang
Keyword(s):  
Inventory Management ◽  
Discrete Distribution ◽  
Transportation Cost ◽  
Inventory Cost ◽  
Inventory Policy ◽  
Penalty Cost ◽  
Manufacturing Enterprises ◽  
Planning Cycle ◽  
Holding Cost ◽  
Inventory Holding

Using the inventory management in a manufacturing enterprise as the application background, this paper mainly studies on the optimal inventory policy for a part. The planning cycle of this problem is limited, and the demand in each planning cycle follows a discrete distribution. The objective is to minimize the inventory cost, namely, the total of transportation cost, inventory holding cost and penalty cost. Based on (s, S) policy, this paper puts forward two different inventory policies for the problem, and establishes two dynamic programming models accordingly. The numerical examples show that the optimal inventory policy significantly reduces the inventory cost.

scholarly journals Mathematical Model of (R,Q) Inventory Policy under Limited Storage Space for Continuous and Periodic Review Policies with Backlog and Lost Sales

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Kanokwan Singha ◽  
Jirachai Buddhakulsomsiri ◽  
Parthana Parthanadee
Keyword(s):  
Lead Time ◽  
Empirical Distribution ◽  
Problem Instance ◽  
Lost Sales ◽  
Storage Space ◽  
Optimal Solutions ◽  
Periodic Review ◽  
Continuous Review ◽  
Mathematical Expressions ◽  
Space Capacity

This paper involves developing new mathematical expressions to find reorder point and order quantity for inventory management policies that explicitly consider storage space capacity. Both continuous and periodic reviews, as well as backlogged and lost demand during stockout, are considered. With storage space capacity, when on-hand inventory exceeds the capacity, the over-ordering cost of storage at an external warehouse is charged on a per-unit-period basis. The objective is to minimize the total cost, consisting of ordering, shortage, holding, and over-ordering costs. Demand and lead time are stochastic and discrete in nature. Demand during varying lead time is modeled using an empirical distribution so that the findings are not subject to assumptions of demand and lead time probability distributions. Due to the complexity of the developed mathematical expressions, the problems are solved using an iterative method. The method is tested with problem instances that use real data from industry. Optimal solutions of the problem instance are determined by performing exhaustive search. The proposed method can effectively find optimal solutions for continuous review policies and near optimal solutions for periodic review policies. Fundamental insights about the inventory policies are reported from a comparison between continuous review and periodic review solutions, as well as a comparison between backlog and lost sales cases.

scholarly journals Multi-Criteria Inventory Optimisation of University of Ibadan, Ibadan, Nigeria’s Bakery Using Goal Programming Approach and Flour as the Major Raw-Material

2021 ◽  
Vol 9 (12) ◽  
pp. 650-660
Author(s):  
*Bolarinwa, Mojisola A. ◽  
Fajebe, Fisayo E.
Keyword(s):  
Goal Programming ◽  
Lead Time ◽  
Raw Materials ◽  
Service Level ◽  
Storage Space ◽  
Time Duration ◽  
Inventory Cost ◽  
Turnover Ratio ◽  
Total Inventory ◽  
University Of Ibadan

Asides inventory cost, which is being used as the only inventory performance measure at the University of Ibadan bakery, a number of other criteria, such as inventory cost, service level, inventory turnover and delivery lead time which influence the performance of an inventory system have surfaced over the years. Hence, there is the need to examine all these criteria-objectives altogether. Therefore, this research was centred towards optimising the inventory system of University of Ibadan bakery, putting multiple criteria into consideration. Data on 17 raw materials: their costs, suppliers, usage rate, lead time, storage space and available capital were collected by means of interviews, past records and observations. The weighted goal program algorithm was adopted to find the best compromise between fulfilling the four objectives by minimising the sum of the deviation from the target values of the goals. Subsequently, Lingo 17.0 and Tora 1.0 optimisation software packages were used to solve and compare the model generated, while putting into consideration storage space constraint and budgeted capital. The developed model from the goal programming algorithm exhibited four goals (combined into one objective function). Same solutions were obtained from Lingo 17.0 and Tora 1.0. While Lingo 17.0 gave a  uniform service level of 100% , a  turnover ratio greater than 1(>1) for all the materials at a negligible increase (of  < 0.0001%) in total inventory cost of the raw materials and available lead time duration of zero days (< 24 hours) for each material, Tora 1.0  gave a  uniform service level of 100% , a  turnover ratio greater than 1 (> 1) for all the materials at a negligible increase (of  < 0.0001%) in total inventory cost of the raw materials and available lead time duration of zero days (< 24 hours) for each material. Implementation of the developed model will eliminate unnecessary waiting time between production, thereby ensuring effective and efficient utilisation of raw materials in production which will lead to reduced cost of holding inventory, elimination of unnecessary overall cost and wastages, and also improvement of the productivity and profit on the long run.

scholarly journals A Procedure for Scheduling Inventory of an Industry by Merging Forecasting and Linear Programming

2020 ◽  
Vol 68 (1) ◽  
pp. 65-70
Author(s):  
AKM Selim Reza ◽  
Sayma Suraiya ◽  
M Babul Hasan
Keyword(s):  
Linear Programming ◽  
Raw Materials ◽  
Minimum Cost ◽  
Inventory Cost ◽  
Model Combining ◽  
Forecasting Method ◽  
Holding Cost ◽  
Optimum Order ◽  
Total Inventory ◽  
Inventory Holding

In this paper, we develop a mathematical model combining forecasting and linear programming for a business organization of Bangladesh to calculate optimum order quantity and inventory cost. We test the model using raw data of the demand for the raw materials and spare inventory for the industry and find out minimum total inventory cost along with ordering cost and inventory holding cost. The developed model make a match between the forecasted demand of raw materials and spare inventory and the minimum total cost of inventory. Finally comparing minimum cost, we observe that our estimated appropriate forecasting method gives optimal inventory cost. Dhaka Univ. J. Sci. 68(1): 65-70, 2020 (January)

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