scholarly journals A Model of Batch Scheduling for a Single Batch Processor with Additional Setups to Minimize Total Inventory Holding Cost of Parts of a Single Item Requested at Multi-due-date

2018 ◽  
Vol 319 ◽  
pp. 012082
Author(s):  
Abdul Hakim Halim ◽  
Ernawati ◽  
Nita P A Hidayat
Keyword(s):  
Batch Scheduling ◽  
Due Date ◽  
Single Item ◽  
Batch Processor ◽  
Holding Cost ◽  
Total Inventory ◽  
Inventory Holding Cost ◽  
Inventory Holding ◽  
Single Batch

scholarly journals Strategic Inventory Positioning in BOM with Multiple Parents Using ASR Lead Time

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jingjing Jiang ◽  
Suk-Chul Rim
Keyword(s):  
Lead Time ◽  
Solution Procedure ◽  
Optimal Position ◽  
Work In Process ◽  
Make To Order ◽  
Holding Cost ◽  
Total Inventory ◽  
Inventory Holding Cost ◽  
Inventory Holding ◽  
Optimal Set

In order to meet the lead time that the customers require, work-in-process inventory (WIPI) is necessary at almost every station in most make-to-order manufacturing. Depending on the station network configuration and lead time at each station, some of the WIPI do not contribute to reducing the manufacturing lead time of the final product at all. Therefore, it is important to identify the optimal set of stations to hold WIPI such that the total inventory holding cost is minimized, while the required due date for the final product is met. The authors have presented a model to determine the optimal position and quantity of WIPI for a given simple bill of material (S-BOM), in which any part in the BOM has only one immediate parent node. In this paper, we extend the previous study to the general BOM (G-BOM) in which parts in the BOM can have more than one immediate parent and present a new solution procedure using genetic algorithm.

scholarly journals The Inventory Routing Problem with Demand Moves

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Annelieke C. Baller ◽  
Said Dabia ◽  
Guy Desaulniers ◽  
Wout E. H. Dullaert
Keyword(s):  
Urban Areas ◽  
Research Literature ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Solution Approach ◽  
Holding Cost ◽  
Inventory Holding Cost ◽  
Problem Instances ◽  
Inventory Holding

AbstractIn the Inventory Routing Problem, customer demand is satisfied from inventory which is replenished with capacitated vehicles. The objective is to minimize total routing and inventory holding cost over a time horizon. If the customers are located relatively close to each other, one has the opportunity to satisfy the demand of a customer by inventory stored at another nearby customer. In the optimization of the customer replenishments, this option can be included to lower total costs. This is for example the case for ATMs in urban areas where an ATM-user that wants to withdraw money could be redirected to another ATM. To the best of our knowledge, the possibility of redirecting end-users is new to the operations research literature and has not been implemented, but is being considered, in the industry. We formulate the Inventory Routing Problem with Demand Moves in which demand of a customer can (partially) be satisfied by the inventory of a nearby customer at a service cost depending on the quantity and the distance. We propose a branch-price-and-cut solution approach which is evaluated on problem instances from the literature. Cost improvements over the classical IRP of up to 10% are observed with average savings around 3%.

Revenue Sharing in a Two-Stage Supply Chain with Linear Stepwise Unit Inventory Holding Cost

2011 ◽  
pp. 254-274
Author(s):  
Jing Hou ◽  
Amy Z. Zeng ◽  
Lindu Zhao
Keyword(s):  
Supply Chain ◽  
Revenue Sharing ◽  
Sequential Optimization ◽  
Inventory Level ◽  
Two Stage ◽  
Channel Relationship ◽  
Holding Cost ◽  
Inventory Holding Cost ◽  
Inventory Holding ◽  
Optimization Mechanism

In this chapter we focus on examining the coordination mechanisms for a two-stage supply chain comprising one supplier and one retailer. We consider such a channel relationship that the transaction quantity between the two members is sensitive to the supplier’s inventory level and that the supplier’s unit inventory holding cost has a linear stepwise structure. We devise a coordinated revenue-sharing contract with bargaining so that each party’s respective profit is better than that resulted from the simple sequential optimization mechanism. The key contract parameters, namely the supplier’s inventory level and the retailer’s revenue-sharing fraction, are obtained and analyzed. Numerical illustrations of the contracts are given and shed lights on how the supply chain should coordinate in order to gain better performance.

Contracts based on Inventory Cost Share for Supply Chain Coordination

2011 ◽  
pp. 126-138 ◽  
Author(s):  
Alejandra Gomez-Padilla
Keyword(s):  
Supply Chain ◽  
Supply Chain Coordination ◽  
The Other ◽  
Inventory Cost ◽  
Cost Share ◽  
Pricing Scheme ◽  
Holding Cost ◽  
Inventory Holding Cost ◽  
Inventory Holding

In this document it is analyzed the importance of contracts for coordination between two companies in a supply chain. In the studied situation, one company, or supplier, supplies one product to the other company, who is a retailer. The companies are going to coordinate by two types of decisions: economic (concerning prices fixed on a contract), and physical exchange (concerning the inventory to be held). Two types of contracts will be presented: one contract with a simple pricing scheme and two contracts with inventory holding cost shared among the companies of the supply chain. The objective is to show that contracts with inventory holding cost share allow the two companies to efficiently coordinate the chain they form.

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.

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.

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