Some Studies in Multi-Storage Inventory System

2016 ◽  
pp. 176-200
Author(s):  
Shyamal Kumar Mondal
Keyword(s):  
Planning Horizon ◽  
Inventory System ◽  
Mixed Integer ◽  
Lot Size ◽  
Continuous Release ◽  
Demand Rate ◽  
Cycle Lengths ◽  
Holding Cost ◽  
Inventory Holding ◽  
And Storage

In this chapter, a multi-storage inventory system has been considered to develop a deterministic inventory model in finite planning horizon. Realistically, it is shown that due to large stock and insufficient space of existing own warehouse (OW); excess items are stored in single rented warehouse (RW). Due to different preserving facilities and storage environment, inventory holding cost is considered to be different in different warehouses. Here, the replenishment cycle lengths are of equal length, the demand rate is a continuous linear increasing function of time and partially backlogged shortages are allowed in all cycles. In each cycle, the replenishment cost is assumed to be dependent linearly on lot size and the stocks of RW are also transported to OW in continuous release pattern. The model is formulated as a constrained non-linear mixed integer cost objective function under single management. Finally, results with a sensitivity analysis have been shown with the help of a real coded GA.

The Study of MTO Online Manufacturers' Guaranteed Delivery Time Model with Order Batching

2014 ◽  
Vol 933 ◽  
pp. 824-829
Author(s):  
Qiang Gang Zhu ◽  
Lei Liu ◽  
Yun Sheng Wang
Keyword(s):  
Lead Time ◽  
Delivery Time ◽  
Lot Size ◽  
Setup Cost ◽  
Time Model ◽  
Holding Cost ◽  
Inventory Holding Cost ◽  
Inventory Holding ◽  
Cost Of Transportation ◽  
Marketing Approach

To MTO on-line manufacturers, one of the most popular time-based competitive strategies is to widely advertise a uniform delivery time guarantee to all the customers. While providing time guarantee can be an effective marketing approach, it is critical for firms to reduce lead time to keep the promise. Decreasing lot size in batching is one of the most important levers to compress lead time in operation. This research expands existing blanket delivery-time guarantee models by integrating operation approach and marketing approach. The online manufacturers guaranteed delivery time model with order batching is established. Some analytic results are provided, and numerical examples are conducted to provide further insight into the problem. The effects of batch processing setup cost, unit inventory holding cost and unit compression cost of transportation time are analyzed. The results indicate that when batch processing setup cost decrease, unit inventory holding cost or unit compression cost of transportation time increase, the online manufacturer should decrease the lot size and shorten the guaranteed delivery time. The customers time and price sensitivities have adverse influences on the manufacturers delivery time decision.

Optimization Methods for Lot-Sizing Problem in an Automated Foundry

2013 ◽  
Vol 58 (3) ◽  
pp. 863-866 ◽  
Author(s):  
J. Duda ◽  
A. Stawowy
Keyword(s):  
Production Planning ◽  
Lot Sizing ◽  
Planning Horizon ◽  
Optimization Methods ◽  
Mixed Integer ◽  
Planning Problem ◽  
Lot Size ◽  
Mip Model ◽  
Production Planning Problem ◽  
Problem Instances

Abstract In the paper we studied a production planning problem in a mid-size foundry that provides tailor-made cast products in small lots for a large number of clients. Assuming that a production bottleneck is the furnace, a mixed-integer programming (MIP) model is proposed to determine the lot size of the items and the required alloys to be produced during each period of the finite planning horizon that is subdivided into smaller periods. As using an advanced commercial MIP solvers may be impractical for more complex and large problem instances, we proposed and compared a few computational intelligence heuristics i.e. tabu search, genetic algorithm and differential evolution. The examination showed that heuristic approaches can provide a good compromise between speed and quality of solutions and can be used in real-world production planning.

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.

scholarly journals Optimizing Inventory Replenishment for Seasonal Demand with Discrete Delivery Times

2021 ◽  
Vol 11 (23) ◽  
pp. 11210
Author(s):  
Mohammed Alnahhal ◽  
Diane Ahrens ◽  
Bashir Salah
Keyword(s):  
Lot Sizing ◽  
Planning Horizon ◽  
Service Level ◽  
Mixed Integer ◽  
Lot Size ◽  
Dynamic Planning ◽  
Holding Costs ◽  
Delivery Times ◽  
Mip Model ◽  
Total Inventory

This study investigates replenishment planning in the case of discrete delivery time, where demand is seasonal. The study is motivated by a case study of a soft drinks company in Germany, where data concerning demand are obtained for a whole year. The investigation focused on one type of apple juice that experiences a peak in demand during the summer. The lot-sizing problem reduces the ordering and the total inventory holding costs using a mixed-integer programming (MIP) model. Both the lot size and cycle time are variable over the planning horizon. To obtain results faster, a dynamic programming (DP) model was developed, and run using R software. The model was run every week to update the plan according to the current inventory size. The DP model was run on a personal computer 35 times to represent dynamic planning. The CPU time was only a few seconds. Results showed that initial planning is difficult to follow, especially after week 30, and the service level was only 92%. Dynamic planning reached a higher service level of 100%. This study is the first to investigate discrete delivery times, opening the door for further investigations in the future in other industries.

Make-To-Order Production Planning With Seasonal Supply In Canned Pineapple Industry

2021 ◽  
Author(s):  
Kanapath Plangsrisakul ◽  
Tuanjai Somboonwiwat ◽  
Chareonchai Khompatraporn
Keyword(s):  
Production Planning ◽  
Planning Horizon ◽  
Labor Cost ◽  
Raw Material ◽  
Supply Uncertainty ◽  
Make To Order ◽  
Total Profit ◽  
Holding Cost ◽  
The Cost ◽  
Inventory Holding

This research studies a make-to-order production planning in a canned pineapple industry. Pineapple is a seasonal perishable fruit. Thus, the cost of fresh pineapple which is the main raw material in canned pineapple is inexpensive during its season. The color of the pineapple also determines the price of the canned pineapple. However, the availability of different colors (called “choice” and “standard”) is dependent. Specifically, if the ratio of the choice color is more, the ratio of the other color is less. There are several costs involve such as fresh pineapple cost, can cost, sugar cost, water cost, labor cost, energy cost, and inventory cost. The problem is formulated as a mathematical model to maximize the total profit over four-months planning horizon. Two supply uncertainty cases are tested which are low and high ratios of the choice color. The results show that the profit depends on available color ratios of the pineapple. The production planning is best if it matches with the availability of the color ratios. In certain months, some fresh pineapple purchased exceed the need of the production because of the dependency of the two colors. The inventory holding cost also influences the production decision—whether to produce the canned pineapple in earlier months or it is better to produce only the canned pineapple when it is needed to serve the customer orders.

scholarly journals Profitability Index Maximization in an Inventory Model with a Price- and Stock-Dependent Demand Rate in a Power-Form

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1157
Author(s):  
Valentín Pando ◽  
Luis A. San-José ◽  
Joaquín Sicilia ◽  
David Alcaide-López-de-Pablo
Keyword(s):  
Cycle Time ◽  
Optimal Policy ◽  
Inventory Model ◽  
Selling Price ◽  
Lot Size ◽  
Financial Investment ◽  
Demand Rate ◽  
Holding Cost ◽  
Optimal Values ◽  
Dependent Demand

This paper presents the optimal policy for an inventory model where the demand rate potentially depends on both selling price and stock level. The goal is the maximization of the profitability index, defined as the ratio income/expense. A numerical algorithm is proposed to calculate the optimal selling price. The optimal values for the depletion time, the cycle time, the maximum profitability index, and the lot size are evaluated from the selling price. The solution shows that the inventory must be replenished when the stock is depleted, i.e., the depletion time is always equal to the cycle time. The optimal policy is obtained with a suitable balance between ordering cost and holding cost. A condition that ensures the profitability of the financial investment in the inventory is established from the initial parameters. Profitability thresholds for several parameters, including the scale and the non-centrality parameters, keeping all the others fixed, are evaluated. The model with an isoelastic price-dependent demand is solved as a particular case. In this last model, all the optimal values are given in a closed form, and a sensitivity analysis is performed for several parameters, including the scale parameter. The results are illustrated with numerical examples.

EOQ MODEL FOR TIME-DEPENDENT DETERIORATION RATE WITH A TEMPORARY PRICE DISCOUNT

2005 ◽  
Vol 22 (04) ◽  
pp. 479-485 ◽  
Author(s):  
BHAVIN J. SHAH ◽  
NITA H. SHAH ◽  
Y. K. SHAH
Keyword(s):  
Fruits And Vegetables ◽  
Price Policy ◽  
Inventory System ◽  
Price Discount ◽  
Marginal Value ◽  
Deterioration Rate ◽  
Eoq Model ◽  
Holding Cost ◽  
The Difference ◽  
Inventory Holding

Deterioration is defined as decay, damage, spoilage, evaporation, obsolescence, pilferage, and loss of utility or loss of marginal value of a commodity that reduces usefulness from original ones. Blood, fish, fruits and vegetables, alcohol, gasoline, radioactive chemicals, medicines, etc., lose their utility with respect to time. In this case, a discount price policy is implemented by the suppliers of these products to promote sales. In this study, a mathematical model is developed for an inventory system that considers a temporary price discount when commodities in an inventory system are subject to deterioration with respect to time. Our goal in this article is to maximize the difference between two costs (gain) — taking advantage of price discount by ordering a large quantity, which in turn increases inventory holding cost as well deterioration cost and by not ordering a large quantity at a discounted price. An attempt is made to find bounds on the beneficial discount rate. The model is supported with a numerical example.

scholarly journals The integrated uncapacitated lot sizing and bin packing problem

2021 ◽  
Author(s):  
Natã Goulart ◽  
Thiago Ferreira de Noronha ◽  
Martin Gomez Ravetti ◽  
Mauricio Cardoso de Souza
Keyword(s):  
Bin Packing ◽  
Lot Sizing ◽  
Packing Problem ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Holding Costs ◽  
Bin Packing Problem ◽  
Combinatorial Relaxation ◽  
The Cost ◽  
Inventory Holding

In the integrated uncapacitated lot sizing and bin packing problem, we have to couple lot sizing decisions of replenishment from single product suppliers with bin packing decisions in the delivery of client orders. A client order is composed of quantities of each product, and the quantities of such an order must be delivered all together no later than a given period. The quantities of an order must all be packed in the same bin, and may be delivered in advance if it is advantageous in terms of costs. We assume a large enough set of homogeneous bins available at each period. The costs involved are setup and inventory holding costs and the cost to use a bin as well. All costs are variable in the planning horizon, and the objective is to minimize the total cost incurred. We propose mixed integer linear programming formulations and a combinatorial relaxation where it is no longer necessary to keep track of the specific bin where each order is packed. An aggregate delivering capacity is computed instead. We also propose heuristics using different strategies to couple the lot sizing and the bin packing subproblems. Computational experiments on instances with different configurations showed that the proposed methods are efficient ways to obtain small optimality gaps in reduced computational times.

scholarly journals A Heuristic for Disassembly Planning in Remanufacturing System

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jinmo Sung ◽  
Bongju Jeong
Keyword(s):  
Computational Efficiency ◽  
Main Idea ◽  
Planning Horizon ◽  
Setup Cost ◽  
Solution Quality ◽  
Purchasing Cost ◽  
Processing Cost ◽  
Holding Cost ◽  
Inventory Holding ◽  
Disassembly Planning

This study aims to improve the efficiency of disassembly planning in remanufacturing environment. Even though disassembly processes are considered as the reverse of the corresponding assembly processes, under some technological and management constraints the feasible and efficient disassembly planning can be achieved by only well-designed algorithms. In this paper, we propose a heuristic for disassembly planning with the existence of disassembled part/subassembly demands. A mathematical model is formulated for solving this problem to determine the sequence and quantity of disassembly operations to minimize the disassembly costs under sequence-dependent setup and capacity constraints. The disassembly costs consist of the setup cost, part inventory holding cost, disassembly processing cost, and purchasing cost that resulted from unsatisfied demand. A simple but efficient heuristic algorithm is proposed to improve the quality of solution and computational efficiency. The main idea of heuristic is to divide the planning horizon into the smaller planning windows and improve the computational efficiency without much loss of solution quality. Performances of the heuristic are investigated through the computational experiments.

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