• Journal of the Korean Operations Research and Management Science Society
• /
• v.32 no.1
• /
• pp.93-104
• /
• 2007

We consider a supply chain where products are shipped to warehouse from manufacturing system to customers. Products are supplied from either in-house regular manufacturing or the secondary source such as subcontractor. The inventory in warehouse is controlled by base-stock policy, that is, whenever a demand arrives from customer, an order is released to the manufacturing system. Unsatisfied demand is backlogged. The manufacturing system is modeled as M/M/s+1/c queueing system, and the orders exceeding the given limit care blocked and lost. The steady state distribution of the outstanding orders and the throughput of the manufacturing system are functions of the level of engagement In the secondary source. There is a profit obtained from throughput and cost not only due to the engagement of the secondary source in the manufacturing system but also inventory positions. We want to maximize the total production profit minus the total cost of the production system by simultaneously determining the optimal level of engagement of the secondary source and the optimal base-stock level of the inventory. We develop two algorithms : one without guarantee of the optimal solution but with the small number of computations, the other optimal but with more computations.

• Journal of the Korea Society for Simulation
• /
• v.12 no.2
• /
• pp.1-11
• /
• 2003

In this paper, we focus an optimal policy focus optimal class of (s, S) inventory control systems. To this end, we use the perturbation analysis and apply a stochastic optimization algorithm to minimize the average cost over a period. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. Our simulation results indicate that the optimal estimates of s and S obtained from a stochastic optimization algorithm are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and review period. Another directions involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

• Journal of Korean Society for Atmospheric Environment
• /
• v.30 no.1
• /
• pp.26-36
• /
• 2014

The uncertainty assessment is important to improve the reliability of emission inventory data. The DARS (Data Attribute Rating System) have recommended as the uncertainty assessment technic of emission inventory by U.S. EPA (Environmental Protection Agency) EIIP (Emission Inventory Improvement Program). The DARS score is based on the perceived quality of the emission factor and activity data. Scores are assigned to four attributes; measurement/method, source specificity, spatial congruity and temporal congruity. The resulting emission factor and activity rate scores are combined to arrive at an overall confidence rating for the inventory. So DARS is believed to be a useful tool and may provide more information about inventories than the usual qualitative grading procedures (e.g. A through E). In this study, the uncertainty assessment for 2009 CAPSS (Clean Air Policy Support System) emission inventory is conducted by DARS. According to the result of this uncertainty assessment, the uncertainty for fugitive dust emission data is higher than other sources, the uncertainty of emission factor for surface coating is the highest value, and the uncertainty of activity data for motor cycle is the highest value. Also it is analysed that the improvement of uncertainty for activity data is as much important as the improvement for emission factor to upgrade the reliability of CAPSS emission inventory.

• Journal of Korean Institute of Industrial Engineers
• /
• v.38 no.2
• /
• pp.89-97
• /
• 2012

This paper considers a manufacturer with a two-station make-to-stock and make-to-order serial production system. The MTS facility produces a single type of component and provides components for the MTO facility that produces customized products. In addition to the internal demand from the MTO facility, the MTS facility faces demands from the spot market with the option of to accept or reject each incoming demand. This paper addresses a joint component inventory rationing and batch production control which maximizes the manufacturer's profit. Using the Markov decision process model, we investigate the structural properties of the optimal inventory rationing and batch production policy, and present two types of heuristics. We implement a numerical experiment to compare the performance of the optimal and heuristic policies and a simulation study to examine the impact of the stochastic process variability on the inventory rationing and batch production control.

• Journal of Korean Institute of Industrial Engineers
• /
• v.5 no.2
• /
• pp.9-14
• /
• 1979

Inventories of finished products exist in each stage of the channel between production and consumption. An inventory has several functions, which make it possible to produce by economic lot size and to elevate services for consumer by shortening delivery time, etc$\cdots$. Finished products may be inventoried in delivery-center as well as at the plant where production takes place. So, finshed products must be dealt with as multistage inventory problem, because an inventory functions differently according to its place. The purpose of this study is to determine how much to carry in stock and what stage to carry Though there may be several channels between production and consumption, this study deals with only one main channel, that is, series of ncomponents and determines the optimal inventory policy by introducing the concept of selling probabilities.

• Journal of Korean Institute of Industrial Engineers
• /
• v.37 no.1
• /
• pp.1-9
• /
• 2011

This paper presents a new method that can solve the integrated problem of combined location routing and inventory problem (CLRIP) efficiently. The CLRIP is used to establish facilities from several candidate depots, to find the optimal set of vehicle routes, and to determine the inventory policy in order to minimize the total system cost. We propose a mathematical model for the CLRIP with budget constrained. Because this model is a nonpolynomial (NP) problem, we propose a endosymbiotic evolutionary algorithm (EEA) which is a kind of symbiotic evolutionary algorithm (SEA). The heuristic method is used to obtaining the initial solutions for the EEA. The experimental results show that EEA perform very well compared to the existing heuristic methods with considering inventory control decisions.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.39 no.1
• /
• pp.83-100
• /
• 2014

Retail shops often experience purchase dependence in which some items are purchased together by customers due to their unknown interior associations. This paper develops an inventory model considering partial backordering under purchase dependence and compares the performance of the inventory model that ignores purchase dependence. Computational analyses show that purchase dependence should be incorporated as an important factor of inventory replenishment policy because the impact of purchase dependence can be more significant as the lost portion of the unmet demand orders increases and the item set is more correlated in terms of order demand.

• Journal of the Korea Safety Management & Science
• /
• v.3 no.3
• /
• pp.77-86
• /
• 2001

An operational strategy for inventory control on finished goods in the distribution system has been given attention to many enterprises and many studies regarding this field have been done and is also on-going currently. Many of these studies represented a large scale distribution network with a unified formulation by using defined symbols. These methods have provided the systematic approach of the distribution network but they are impossible to applying the reality system due to not considering the service rate of demand and treating the shortage of inventory. In order to overcome these unrealistic problems, the novel safety stock policy of responding to customers' inventory distribution network is suggested. this paper explores the transportation between Central Distribution Center(CDC) and Regional Distribution Center(RDC). Especially, the relation of transportation cost between CDC and RDC and cost of inventory control according to safety inventory with service level are emphasized. We could obtain the good results of this study by determining the optimal safety stock considering the various variables and constraints.

• Industrial Engineering and Management Systems
• /
• v.15 no.4
• /
• pp.354-363
• /
• 2016

Due to uncertain environment, various parameters such as price, queuing length, warranty, and so on influence on inventory models. In this paper, an inventory-queuing-pricing problem with continuous review inventory control policy and batch arrival queuing approach, is presented. To best of our knowledge, (I) demand function is stochastic and price dependent; (II) due to the uncertainty in real-world situations, a fuzzy programming approach is applied. Therefore, the presented model with goal of maximizing total profit of system analyzes the price and order quantity decision variables. Since the proposed model belongs to NP-hard problems, Pareto-based approaches based on non-dominated ranking and sorting genetic algorithm are proposed and justified to solve the model. Several numerical illustrations are generated to demonstrate the model validity and algorithms performance. The results showed the applicability and robustness of the proposed soft-computing-based approaches to analyze the problem.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.1
• /
• pp.108-117
• /
• 2014

This study considers warehouse sizing decisions in an integrated single vendor-single buyer production inventory system by incorporating new decision variables and constraints associated with warehouse size into the formulations. Two typical inventory control policies proposed in the literature (i.e., Identical Delivery Quantity and Deliver What is Produced) have been investigated with consideration of warehouse investment costs. The numerical study shows that Deliver What is Produced is less flexible than Identical Delivery Quantity, resulting in the conclusion that the latter would be preferable when considering warehouse investment costs.