The economic production and pricing model with lot-size-dependent production cost

2011 ◽  
Vol 54 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Alireza Kabirian
2008 ◽  
Vol 25 (05) ◽  
pp. 673-688 ◽  
Author(s):  
B. C. OUYANG ◽  
H. RAU

It is common that prices of raw materials, parts or products decrease significantly after they come onto the market. High technology products are good examples, such as PCs, CPUs, DRAM, and mobile phones. Consequently, the traditional economic production quantity (EPQ) model assuming a constant unit production cost is no longer suitable for today's time-based competition. This study incorporates linearly and exponentially decreasing unit production costs during the mature stage of a product life cycle and presents a mathematical inventory model for production policy. A recursive algorithm is developed to obtain the optimal production schedule and a one-dimension search method is applied to find the optimal number of production cycles. In addition, numerical examples to illustrate the proposed model and its significance with or without considering a continuous reduction in unit production costs for the production policy are discussed as well.


2019 ◽  
Vol 4 (2) ◽  
pp. 205-214
Author(s):  
Erika Fatma

Lot sizing problem in production planning aims to optimize production costs (processing, setup and holding cost) by fulfilling demand and resources capacity costraint. The Capacitated Lot sizing Problem (CLSP) model aims to balance the setup costs and inventory costs to obtain optimal total costs. The object of this study was a plastic component manufacturing company. This study use CLSP model, considering process costs, holding costs and setup costs, by calculating product cycle and setup time. The constraint of this model is the production time capacity and the storage capacity of the finished product. CLSP can reduce the total production cost by 4.05% and can reduce setup time by 46.75%.  Keyword: Lot size, CLSP, Total production cost.


2016 ◽  
Vol 15 (1) ◽  
pp. 78 ◽  
Author(s):  
Nurike Oktavia ◽  
Henmaidi Henmaidi ◽  
Jonrinaldi Jonrinaldi

The most popular inventory model to determine production lot size is Economic Production Quantity (EPQ). It shows enterprise how to minimize total production cost by reducing inventory cost. But, three main parameters in EPQ which are demand, machine set up cost, and holding cost, are not suitable to solve issues nowadays. When an enterprise has two types of demand, continue and discrete demand, the basic EPQ would be no longer useful. Demand continues comes from a customer who wants their needs to be fulfilled every time per unit time, while the fulfillment of demand discrete is at a fixed interval of time. A literature review is done by writers to observe other formulation of EPQ model. As there is no other research can be found which adopt this topic, this study tries to develop EPQ model considering two types of demand simultaneously.


Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1014
Author(s):  
Ibrahim Alharkan ◽  
Mustafa Saleh ◽  
Mageed Ghaleb ◽  
Abdulsalam Farhan ◽  
Ahmed Badwelan

This study analyzes a stochastic continuous review inventory system (Q,r) using a simulation-based optimization model. The lead time depends on lot size, unit production time, setup time, and a shop floor factor that represents moving, waiting, and lot size inspection times. A simulation-based model is proposed for optimizing order quantity (Q) and reorder point (r) that minimize the total inventory costs (holding, backlogging, and ordering costs) in a two-echelon supply chain, which consists of two identical retailers, a distributor, and a supplier. The simulation model is created with Arena software and validated using an analytical model. The model is interfaced with the OptQuest optimization tool, which is embedded in the Arena software, to search for the least cost lot sizes and reorder points. The proposed model is designed for general demand distributions that are too complex to be solved analytically. Hence, for the first time, the present study considers the stochastic inventory continuous review policy (Q,r) in a two-echelon supply chain system with lot size-dependent lead time L(Q). An experimental study is conducted, and results are provided to assess the developed model. Results show that the optimized Q and r for different distributions of daily demand are not the same even if the associated total inventory costs are close to each other.


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