• 산업경영시스템학회지
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• 제42권1호
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• pp.64-73
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• 2019

The manufacturing companies under Make-To-Order (MTO) production environment face highly variable requirements of the customers. It makes them difficult to establish preemptive production strategy through inventory management and demand forecasting. Therefore, the ability to establish an optimal production schedule that incorporates the various requirements of the customers is emphasized as the key success factor. In this study, we suggest a process of designing the simulation model for establishing production schedule and apply this model to the case of a flat glass processing company. The flat glass manufacturing industry is under MTO production environment. Academic research of flat glass industry is focused on minimizing the waste in the cutting process. In addition, in the practical view, the flat glass manufacturing companies tend to establish the production schedule based on the intuition of production manager and it results in failure of meeting the due date. Based on these findings, the case study aims to present the process of drawing up a production schedule through simulation modeling. The actual data of Korean flat glass processing company were used to make a monthly production schedule. To do this, five scenarios based on dispatching rules are considered and each scenario is evaluated by three key performance indicators for delivery compliance. We used B2MML (Business To Manufacturing Markup Language) schema for integrating manufacturing systems and simulations are carried out by using SIMIO simulation software. The results provide the basis for determining a suitable production schedule from the production manager's perspective.

• 한국경영과학회지
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• 제9권2호
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• pp.15-22
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• 1984

A deterministic multiproduct, facility-in series multiperiod production planning model is analyzed, where each period demand for the product of a facility appear in a fixed proportion of that for the product of the immediately following facility. The model considers concave production and inventory costs, which can depend upon the production in different facilities. No backlogging is allowed. It is shown that the model is represented via a single source network, which facilitates development of efficient dynamic programming algorithms for computing the optimal production schedule.

• 한국경영과학회지
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• 제37권1호
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• pp.1-18
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• 2012

The present study provides some extensions over a recent work in Won (2011) which investigates properties of the static newsvendor problem under a schedule involving progressive multiple discounts under the assumption that demand is given exogenously. Khouja (1995, 1996) formulated the extended versions over the classical newsvendor model with various discount policies including all-units discount and/or multiple discounts and found that the extended newsvendor models with discount schedules yield higher optimal expected profits than the classical newsvendor model with no-discounts. In this study, we establish a robust conjecture as a stronger statement than Khouja's findings with regard to the general relationship among the expected profits of newsvendor models in the sense that the conjecture holds for every order quantity as well as the optimal order quantity. The conjecture encourages the newsvendor facing quantity discounts to safely implement her own discounts policy to customer or accept quantity discounts offered by the supplier even if the optimal order quantity cannot be ordered due to additional restrictions such as budget or warehouse capacity constraints because the newsvendor models with quantity discounts always yield higher expected profit than the classic newsvendor model without quantity discounts regardless of the order quantity. Results from wide experiments with various probability distributions of demand strongly support our conjecture.

• 대한산업공학회지
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• 제41권5호
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• pp.414-424
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• 2015

In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.686-692
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• 2002

Disassembly scheduling is the problem of determining the ordering and disassembly schedules of used products while satisfying the demand of their parts of components over a certain planning horizon. The objective is to minimize the sum of purchase, setup, disassembly operation and inventory holding costs. This paper considers products with assembly structure, i.e. products without parts commonality, and suggests a heuristic in which an initial solution is obtained in the form of the minimal latest disassembly schedule, and then improved considering trade-offs among different cost factors. To show the performance of the heuristic suggested in this paper, computational experiments were done on the modified existing examples and the results show that the heuristic can give optimal of very near optimal solutions within very short computation times.

• 상하수도학회지
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• 제25권4호
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• pp.581-589
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• 2011

Generally, treated water or raw water is transported into storage reservoirs which are receiving facilities of local governments from multi-regional water supply systems. A water supply control and operation center is operated not only to manage the water facilities more economically and efficiently but also to mitigate the shortage of water resources due to the increase in water consumption. To achieve the goal, important information such as the flow-rate in the systems, water levels of storage reservoirs or tanks, and pump-operation schedule should be considered based on the resonable water demand forecasting. However, it is difficult to acquire the pattern of water demand used in local government, since the operating information is not shared between multi-regional and local water systems. The pattern of water demand is irregular and unpredictable. Also, additional changes such as an abrupt accident and frequent changes of electric power rates could occur. Consequently, it is not easy to forecast accurate water demands. Therefore, it is necessary to introduce a short-term water demands forecasting and to develop an application of the forecasting models. In this study, the forecasting simulator for water demand is developed based on mathematical and neural network methods as linear and non-linear models to implement the optimal water demands forecasting. It is shown that MLP(Multi-Layered Perceptron) and ANFIS(Adaptive Neuro-Fuzzy Inference System) can be applied to obtain better forecasting results in multi-regional water supply systems with a large scale and local water supply systems with small or medium scale than conventional methods, respectively.

• 한국통신학회논문지
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• 제32권11B호
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• pp.709-717
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• 2007

네트워크 서비스의 요금제는 경제적 효율성과 더불어 네트워크의 혼잡 제어라는 목적도 가지고 있다. 사용자들에 의해 공유되는 링크를 기반으로 네트워크 서비스를 제공하는 독점 공급자는 링크의 대역폭 제약 하에서 수익을 극대화하면서 사용자가 요구한 대역폭을 보장할 수 있는 요금제를 필요로 한다. 이 경우 비선형 요금제는 서비스 제공자의 목적과 사용자들의 다양한 요구를 만족시킬 수 있는 효율적인 요금제이다. 본 연구에서는 대역폭을 제공하는 네트워크 서비스에서 공유 링크의 대역폭 제약이 존재할 때 비선형 요금제가 어떻게 적용될 수 있는지 효용함수와 사용자 수요 특성의 확률 분포를 중심으로 살펴보고, 사용자의 수요 특성이 멱급수 법칙을 따르는 경우 비선형 요금제의 결과로 단위 대역폭당 가격이 일정한 선형 요금제가 나타날 수 있음을 보인다. 또한 사용자의 수요 분포에 대한 불완전한 정보를 가진 서비스 제공자가 네트워크의 혼잡도로부터 최적 요금제를 찾는 방법을 소개하고, 연구 결과에 근거하여 인터넷의 발전 방향과 인터넷 요금제의 관계를 생각한다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 봄 학술발표논문집 Vol.29 No.1 (A)
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• pp.676-678
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• 2002

In this work, we present the novel scheduling algorithm of the multimedia data retrieval for the mobile disk drive. Our algorithm is focused on minimizing the power consumption involved in data retrieval from the local disk drive. The prime commodity in mobile devices is the electricity. Strict restriction on power consumption requirement of the mobile device put unique demand in designing of its hardware and software components. State of the art disk based storage subsystem becomes small enough to be embedded in handhold devices. It delivers abundant storage capacity and portability. However, it is never be trivial to integrate small hard disk or optical disk drive in handhold devices due to its excessive power consumption. Our algorithm ARM in this article generates the optimal schedule of retrieving data blocks from the mobile disk drive while guaranteeing continuous playback of multimedia data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.19-21
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• 2000

This paper presents a game theory application for analyzing power transactions and market design in a deregulated energy marketplace such as PoolCo. The conventional least-cost approaches for the generation resource schedule can not exactly handle recent real-world situations. A systematic tool using game theory for the market participants is presented such that it determines the net profits through the optimal bidding strategies including the strategies for the bidding prices and bidding generations. We treat this power transaction game as incomplete information one, which means each market participants does not know other's cost function. And the demand elasticity of the energy price is considered for the realistic modeling of the deregulated marketplace.

• 한국유통학회:학술대회논문집
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• 한국유통학회 2000년도 추계학술대회 발표논문집
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• pp.91-105
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• 2000

Results of a study of the coordination effect in stocking and promotional markdown policies for a supply chain consisting of a retailer and a discount outlet (DCO) are reported here. We assume that the products are sold in two consecutive periods: Normal Sales Period (NSP) and subsequent Promotional Sales Period (PSP). When managers in the two periods coordinate, they share information on the demand forecast and jointly decide the stocking quantity, markdown time schedule, and markdown price to maximize mutual profit. In the absence of coordination, decisions are decentralized to optimize the individual party's objective function. Optimal coordination policy for the retailer/DCO problem setting is analyzed, and the coordination policy is compared with the uncoordinated policy to explore factors that make coordination an effective approach.