Earticle

In system design, it is not always possible that all decision makers can cooperate fully and thus avoid conflict. They each control a specified subset of design variables and seek to minimize their own cost functions subject to their individual constraints. However, a system management team makes every effort to coordinate multiple disciplines and overcome such noncooperative environment. Although full cooperation is difficult to achieve, noncooperation also should be avoided as possible. Our approach is to predict the results of their cooperation and generate approximate Pareto set for their multiple objectives. The Pareto set can be obtained according to the degree of one's conceding coupling variables in the other's favor. We employ approximation concept for modelling this coordination and the mutiobjective genetic algorithm for exploring the coupling variable space for obtaining an approximate Pareto set. The approximation management concept is also used for improving the accuracy of the Pareto set. The exploration for the coupling variable space is more efficient because of its smaller dimension than the design variable space. Also, our approach doesn't force the disciplines to change their own way of running analysis and synthesis tools. Since the decision making process is not sequential, the required time can be reduced comparing to the existing multidisciplinary design optimization. This approach is applied to some mathematical examples and structural optimization problems.

본 연구는 한국의 자동차 산업의 규모의 경제와 범위의 경제에 관한 실증연구이다. 한국의 5대 자동차 회사인 현대, 기아, 대우, 삼성, 쌍용 자동차에 대하여 비용함수를 추정하였다. 추정결과는 다음과 같다. 첫째, 한국의 자동차 회사는 40년 동안 상당한 발전을 해왔으며 규모의 경제를 보이고 있다. 둘째, 자동차 산업 전반에 걸쳐서 소형차와 대형차 조합에서, 트럭과 소형차, 대형차 조합에서 범위의 비 경제가 존재하며 각 회사 수준에서도 소형차, 대형차, 트럭 조합에서 범위의 비 경제가 존재하는 것으로 추정되었다. 본 연구의 연구 결과는 한국 자동차 산업의 비용구조, 기술, 생산성에 대하여 상당한 정보를 제공한다고 할 수 있다.

The purpose of this study is to analyze the economy of scale and scope in the Korean automobile industry. We estimate the cost function of the five Korea automobile maker. The estimation results are follows. First, the Korean automobile industry has grown rapidly during 40 years and there is an economy of scope in the production ion combination of truck and small car. large car and there is an diseconomy of scope in the production combination of large car and small car, truck.

기계학습은 학습에 이용되는 학습 데이터와 데이터를 예측할 인공신경망을 이용하여 비용함수를 만들고, 비용함 수를 최소화시키는 파라미터들을 찾는 과정이다. 파라미터들은 비용함수의 그래디언트 기반 방법들을 이용하여 변화하 게 된다. 디지털 신호가 복잡할수록, 학습하고자 하는 문제가 복잡할수록, 인공신경망의 구조는 더욱 복잡해지고 깊어진 다. 복잡하고, 깊어지는 인공신경망 구조는 과적합(Over-fitting) 문제를 발생시킨다. 과적합 문제를 해결하기 위하여 파라미터의 가중치 감소 정규화 방법이 사용되고 있다. 우리는 이러한 방법에서 추가로 비용함수의 값을 이용한다. 이러 한 방법으로 기계학습의 정확도가 향상되는 결과를 얻었으며 이는 수치 실험을 통하여 우수성이 확인된다. 이러한 결과 는 기계학습을 통한 인공지능의 폭넓은 데이터에 대한 정확한 값을 도출한다.

Machine learning is the process of constructing a cost function using learning data used for learning and an artificial neural network to predict the data, and finding parameters that minimize the cost function. Parameters are changed by using the gradient-based method of the cost function. The more complex the digital signal and the more complex the problem to be learned, the more complex and deeper the structure of the artificial neural network. Such a complex and deep neural network structure can cause over-fitting problems. In order to avoid over-fitting, a weight decay regularization method of parameters is used. We additionally use the value of the cost function in this method. In this way, the accuracy of machine learning is improved, and the superiority is confirmed through numerical experiments. These results derive accurate values for a wide range of artificial intelligence data through machine learning.

본 연구는 선형스플라인 비용함수를 이용하여 우리나라 은행산업의 규모 및 범위의 경제 여부를 분석하였다. 선형스플라인 함수는 트랜스로그 함수의 한계를 극복하면서도 우리나라와 같이 표본 크기가 작은 경우에 작은 모수를 가지고도 여러 추세를 잘 추정할 수 있다는 강점을 가지고 있다. 실증분석 결과, 선형스플라인의 경우 우리나라 시중은행, 지방은행은 모두 규모의 경제가 있는 것으로 분석되었다. 시중, 지방은행 간에는 지방은행이 시중은행에 비해 상대적으로 높은 규모의 경제를 확보하고 있는 것으로 나타났다. 외환위기 이전(1987년～1997년), 본격적인 구조조정기(1998년～2000년), 구조조정 진정기(2001년～2004년) 등 기간별로도 모든 기간에 걸쳐 규모의 경제가 있는 것으로 나타났다. 다음으로, 선형스플라인을 이용한 범위의 경제는 계산 방식에 따라 그 값이 상이해 범위의 경제가 있다고 단정하기 어렵다. 전통적 방식의 경우 시중, 지방은행은 모두 범위의 경제가 없으나, 확장경로 준가법성의 경우에는 범위의 경제가 있는 것으로 분석되었다. 시기별로는 외환위기 이전에는 계산 방식에 따라 상반된 결과가 나타났으나, 외환위기 이후에는 범위의 경제가 없는 것으로 분석되었다.

This paper examines the economies of scale and scope in Korea’s banking industry by applying a spline cost function approach with other widely-used cost functions, such as the translog and Fourier cost functions. One advantage of the spline function technique is that it overcomes the limitations of the translog function. It also has ability to better identify a variety of trends with smaller parameters than the Fourier function even when the sample size is small.The results, based on the spline cost function, indicate that there exists an economy of scale in Korea's banking industry. Regional banks have a relatively greater economy of scale than nationwide banks. The economies of scale exist in the banking industry across time periods：pre-financial crisis period of 1987～1997, between 1998 to 2000 when restructuring in the banking industry was earnestly promoted, and the final stage of restructuring in 2001～2004. However, our study does not show significant evidence of existence of scope economies, in that two different approaches do not produce the same conclusion. That is, the classical measure of scope economies finds no economies of scope for both nationwide and regional banks, whereas another measure of scope economies, called expansion path subadditivity, indicates there exists an economy of scope for both nationwide and regional banks. The economies of scope are found prior to the financial crisis in 1997 with the results differing based on the two measures. However, our study finds no economies of scope in the times following the crisis. 攀* Sogang University, College of Business Administration

Now days, the marketing environment is rapidly changed. Therefore, a lot of companies try to reduce production cost. Especially, Design is a important activities in new product development. While the concepts of design for manufacturable and concurrent engineering have made significant advances in integrating the design function with other areas in the firm. There are still major gaps in timely and accurate costing information available to designers. Inappropriate design could result in high redesign cost and delay in product relation. The generation of design and improvement is a time-consuming and mentally exhaustion process. It involves combining design features to generate as many potential design as possible. As not all features combinations are feasible, decision-makers have to narrow down the potential solutions and subsequently select appropriate design for further development. This new study is composed of 3 steps aiming at the Low Cost Design of the product. The three steps are consisted that setting up the target Cost, estimating the current functional cost, the design of a unit's reviewing according to the priority of the difference between the target cost and the functional cost.

This paper presents an analytic method of quality function deployment(QFD) that is to maximize customer satisfaction subject to technical and economic sides in process design. We have used Wasserman's normalization method and the analytical hierarchy process(AHP) to determine the intensity of the relationship between customer requirements and process design attributes. This paper also shows cost-quality model the tradeoff between quality and cost as a linear programming(LP) with new constraints that have designated special process required allocating firstly. The cost-quality function deployment of piston ring is presented to illustrate the feasibility of such techniques.

This paper presents an analytic method of quality function deployment(QFD) that is to maximize customer satisfaction subject to technical and economic sides in process design. We have used Wasserman's normalization method and the analytical hierarchy process(AHP) to determine the intensity of the relationship between customer requirements and process design attributes. This paper also shows cost-quality model the tradeoff between quality and cost as a linear programming(LP) with new constraints that have designated special process required allocating firstly The cost-quality function deployment of piston ring is presented to illustrate the feasibility of such techniques.

This paper presents a method which optimizes the cost allocation in the design process of a metal curtain-wall unit using Quality Function Deployment (QFD) method. From the literature survey, it was found that previous researches have been focused on maximizing customer-satisfaction using QFD without considering the constrained budget. This paper describes how the limited budget condition is considered in the QFD process for a curtain wall design. A case study is presented to demonstrate the applicability of the method proposed by the authors. The method contributes to deliver the curtain-wall design in a way to satisfy the level of requirements of both the customer and the curtain-wall contractor by calculating a solution vector allocating limited budget to the Technical Attributes(TAs) of the curtain wall unit according to the importance weight of Customer Attributes(CAs).

This paper proposes an optimal fire escape algorithm based on the A* pathfinding algorithm in building fire situations. This algorithm uses building map coordinates to generate the escape path while ignoring diagonal directions. A potential function is calculated by considering situational factors, such as fire location, smoke, and heat information, to estimate the effect on the user’s escapability based on his or her location within the building. The calculated potential function determines the path with the lowest cost and illuminates the escape route with leading lights to aid the user to escape hazardous situations that might cause loss of orientation. The proposed algorithm suggests safer, shorter paths and aims to safely lead people to exits while minimizing the dangers of smoke and poisonous gases inside buildings. The coordinates of a real-life building environment were obtained to prove the effectiveness of the escape-route algorithm. Simulation results provided different lowest-cost paths based on various building fire situations.

Developing a system architecture that satisfies the functional requirements and keeping the quality attributes high is still an open challenge.The task of selecting the optimal combination and redundancy levels of components (which is known as RAP problem) that meet system-level constraints is hard since each one of these alternatives must be modeled in order to obtain the global optimal solution. This problem is classified as NP-complete and many researches have suggested use of metaheuristic to encode this challenge as an optimization problem for improving architectures. The search for optimal solution in metaheuristics techniques is guided by objective function/functions. Majority of studies in RAP area were focused on reliability and mostly simple cost functions were used. An adopted cost-with-discount function is proposed in this paper to increase the efficiency of the approach within especial conditions. Single Objective - Particle Swarm Optimization (SO-PSO) to automatically generate and to evaluate architecture is implemented in order to support design decision. The Anti-lock Breaking System (ABS) has been used as a case study to motivate, demonstrate the applicability, and to validate the study. And statistical t-test is performed to evaluate the approach. The evaluation of the approach has proven that; it is significantly impact on providing an efficient solution and it can be used to assist architectures to easily achieve their objectives since they can decide on the automatically provided design options according to technical and financial inclinations.

In this paper, a Cuckoo Search Algorithm (CSA) is proposed for solving environmental economic load dispatch (EELD) problem with quadratic fuel function. Cuckoo Search is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species for solving optimization problems with promising results. However, Cuckoo Search has not been applied to EELD problem so far. Therefore, the paper presents application of CSA to the problem. The effectiveness of the proposed method is tested on several cases of dispatch and loads. The obtained result including fuel cost, emission and computation time from CSA are compared to those from other method reported in the paper. The comparison result has indicated that the proposed CSA is a very efficient method for solving EELD problem.

This paper proposes a Modified Differential Evolution (MDE) for solving multi-objective load dispatch (MOLD) problem where transmission power losses are considered. MDE is an improved version of conventional Differential Evolution (CDE) in which the mutation operation of the CDE is improved by using five differential solutions instead of three ones similar to CDE. In the MOLD problem, three cases of dispatch including economic dispatch, emission dispatch and multi-objective dispatch are carried out by considering fuel cost function, emission function and both fuel cost and emission functions. In the third case of dispatch, there is a price penalty factor employed to determine the best compromise solution instead of using Fuzzy-based mechanism similar to other studies. The performance of MDE is verified by testing on two systems with three units and one system with six units. In the two systems, the fuel cost and emission from MDE are compared to those from CDE and other existing meta-heuristic algorithms, and the analysis on the result comparison indicates that the MDE is a promising algorithm for solving the MOLD problem.

Software applications have a huge and inseparable impact on our lives. The complexity of the applications increases rapidly to support high performance and multifunction. Accordingly, the cost model for applications is increasingly important. Line of Code (LOC) and Man-Month (M/M) as the cost model measure the quantitative sides of the applications. Unlike them, Function Point (FP) measures the functionalities of the application. FP is efficient for estimating qualitative characteristics, but it is restricted to measuring the cost of an application using the wireless data broadcast which can support any number of clients. In this paper, we propose, a Function Point model for Information services using wireles data Broadcast (FPIB) to measure the development cost of an application that serves using the wireless data broadcast environment. FPIB adopts critical parameters of the wireless broadcast environment and the complexity of them to measure effectively the cost developing the application. Through the evaluation comparing the proposed FPIB with FP, we reveal the effectiveness of the proposed FPIB.

본 논문은 운전금지영역을 가진 이차 볼록 발전비용 함수를 적용하는 경제급전의 최적화 문제에 대한 결정론적 최적화 알고리즘을 제안하였다. 제안된 알고리즘은 운전금지구역을 가진 발전기는 운전금지구역을 벗어나도록 분할하고, 초기치 P _{i} larrow P _{i} ^{max}에 대해 발전단가가 큰 순서대로 발전량을 감소시키고, {} _{max} LEFT { F(P _{i} )-F(P _{i} - beta ) RIGHT } > _{min} LEFT { F(P _{j} + beta ) RIGHT LEFT. -F(P _{j} ) RIGHT } ,`i != j,`beta =1.0,`0.1,`0.01,`0.001에 대해 P _{i} larrow `P _{i} - beta ,`P _{j} ` larrow P _{j} + beta 의 교환 최적화 과정을 수행하였다. 제안된 방법을 15-발전기의 3가지 사례에 적용한 결과 간단하면서도 항상 동일한 결과로 휴리스틱 알고리즘들에 비해 최적의 결과를 나타내었다.

This paper proposes a deterministic optimization algorithm to solve economic load dispatch problem with quadratic convex fuel cost function. The proposed algorithm primarily partitions a generator with prohibited zones into multiple generators so as to place them afield the prohibited zone. It then sets initial values to P _{i} larrow P _{i} ^{max} and reduces power generation costs of those incurring the maximum unit power cost. It finally employs a swap optimization process of P _{i} larrow `P _{i} - beta ,`P _{j} ` larrow P _{j} + beta where {} _{max} LEFT { F(P _{i} )-F(P _{i} - beta ) RIGHT } > _{min} LEFT { F(P _{j} + beta ) RIGHT .LEFT. -F(P _{j} ) RIGHT } ,`i != j,`beta =1.0,`0.1,`0.01,`0.001 . When applied to 3 different 15-generator cases, the proposed algorithm has consistently yielded optimized results compared to those of heuristic algorithms.

본 논문은 기존의 CMA(Constant Modulus Algorithm) 적응 등화기 성능인 수렴 특성과 잔류 부호간 간섭의 영향을 경감시키기 위해 비용 함수를 개선한 ACMA(Advanced CMA)에 관한 것이다. CMA는 진폭만을 보상하고 위상은 보상을 하지 못하며, RCA(Reduced Constellation Algorithm)는 진폭과 위상을 보상 하지만 수렴 특성이 불안한 문제점이 있다. CMA의 단점인 위상의 문제를 해결키 위한 MCMA는 실수부와 허수부를 따로 처리하여 진폭과 위상을 보상하지만 하드웨어의 복잡도와 진폭의 보상 능력에서는 CMA보다 열악해지는 문제점이 있다. 제안하는 ACMA에서는 CMA와 MCMA(Modified CMA) 알고리즘 장점만을 살릴 수 있도록 비용 함수를 개량하여 진폭과 위상의 보상, 빠른 수렴 속도 및 잔류 ISI 감소와 양호한 심볼 오류율 (SER) 특성을 얻을 수 있음을 컴퓨터 시뮬레이션으로 확인하였다.

In this paper, the concerned CMA (Constant Modulus Algorithm) adaptive equalizer convergence rate and residual inter-symbol interference using cost function in order to improved to the ACMA (Advanced CMA). The CMA method compensates amplitude but does not compensate phase. On the other hand, The RCA(Reduced Constellation Algorithm) method compensates both the amplitude and the phase but it has the convergence rate problem. MCMA method is a way to solve the phase problem of CMA method compensates both the amplitude and the phase after respectively calculating the real and imaginary components. But it is more than poor CMA method in the complexity of hardware and the compensation performance. The cost function can advantages by improving the CMA and a MCMA (Modified CMA) equalizer so that the amplitude and phase retrieval the equalization steady-state to reduce the error by using ISI and faster convergence rate and performance is good SER (Symbol Error Ratio) was confirmed by computer simulations .

본 논문은 이차 발전비용 함수를 적용하는 경제급전의 최적화 문제에 대한 균형-교환 최적화 알고리즘을 제안하였다. 제안된 알고리즘은 초기치 , 에 대해 일 때까지 , 인 발전기 의 출력량을 로 균형과정을 수행하고, 교환과정은 에 대해 로 수행하였다. 제안된 방법을 15, 20과 38-발전기 사례에 적용한 결과 간단하면서도 항상 동일한 결과로 가장 좋은 결과를 나타내었다. 또한, 73-발전기를 통합하여 경제급전을 수행한 결과 독립적으로 운영하는 경우에 비해 발전비용을 현저히 절약할 수 있음을 보였다.

In this paper, I devise a balance-swap optimization (BSO) algorithm to solve economic load dispatch with a quadratic fuel cost function. This algorithm firstly sets initial values to , and subsequently entails two major processes: a balance process whereby a generator’s power of , is balanced by until ; and a swap process whereby is set at . When applied to 15, 20, and 38-generators benchmark data, this simple algorithm has proven to consistently yield the best possible results. Moreover, this algorithm has dramatically reduced the costs for a centralized operation of 73-generators – a sum of the three benchmark cases – which could otherwise have been impossible for independent operations.

본 논문은 복잡한 비평활 발전비용함수를 가진 경제급전의 최적화 문제를 풀기 위해 단순히 선형 근사함수를 이용하는 방법을 제안하였다. 제안된 알고리즘은 비평활 발전비용 함수를 선형으로 근사시키고, 요구량이 현재의 발전 량을 초과하는 경우 발전단가가 비싼 발전기의 가동을 중지시키고, 발전단가가 보다 큰 발전기의 발전량을 감소시켜 요구량과 발전량의 균형을 맞추는 개념을 도입하였다. 경제급전 문제의 시험사례로 빈번히 활용되고 있는 데이터에 대 해 제안된 알고리즘을 적용한 결과 기존의 휴리스틱 알고리즘의 최적화 해를 획기적으로 감소시킬 수 있었으며, 현재 실무적으로 적용되고 있는 2차 평활함수 근사법과 유사한 결과를 얻었다.

This paper proposes a simple linear function approximation method to solve an economic load dispatch problem with complex non-smooth generating cost function. This algorithm approximates a non-smooth power cost function to a linear approximate function and subsequently shuts down a generator with the highest operating cost and reduces the power of generator with more generating cost in order to balance the generating power and demands. When applied to the most prevalent benchmark economic load dispatch cases, the proposed algorithm is found to dramatically reduce the power cost than does heuristic algorithm. Moreover, it has successfully obtained results similar to those obtained through a quadratic approximate function method.

비 볼록 발전비용함수에 대한 최적화 문제는 다항시간으로 해를 구하는 알고리즘이 알려져 있지 않아 전기 분야에서는 부득이 2차 함수만을 사용하고 있다. 본 논문은 비 볼록 발전비용함수의 경제급전 최적화 문제에 대한 밸브지점 최적화 알고리즘을 제안하였다. 제안된 알고리즘은 초기 치로 최대 발전량 Pi ←Pi max로 설정하고, 평균 발전단가가 max Ci 인 발전기 i의 발전량을 밸브지점 Pik로 감소시키는 방법을 적용하였다. 제안된 알고리즘을 13과 40-발전기 데이터에 적용한 결과 기존의 휴리스틱 알고리즘보다 좋은 성능을 보였다. 따라서 비 볼록 발전비용함수의 경제급전 문제 최적 해는 각 발전기의 밸브지점 발전량으로 수렴함을 보였다.

There is no polynomial-time algorithm that can be obtain the optimal solution for economic load dispatch problem with non-convex fuel cost functions. Therefore, electrical field uses quadratic fuel cost function unavoidably. This paper proposes a valve-point optimization (VPO) algorithm for economic load dispatch problem with non-convex fuel cost functions. This algorithm sets the initial values to maximum powers Pi ←Pi max for each generator. It then reduces the generation power of generator with an average power cost of max Ci to a valve point power Pik. The proposed algorithm has been found to perform better than the extant heuristic methods when applied to 13 and 40-generator benchmark data. This paper consequently proves that the optimal solution to economic load dispatch problem with non-convex fuel cost functions converges to the valve-point power of each generator.

본 연구는 RFID 리더에서 머신 팩터(Machine Factor)와 맨 팩터(Man Factor)를 네트웍상으로 실시간 전송하여 정확한 원가 계산이 가능하도록 한 실시간 생산 원가 계산 기능을 갖는 생산관리시스템에 관한 것이다. 이를 위하여 본 연구는 생산 설비 제어장치에 마이크로프로세서를 도입하였고, 생산 설비의 일측에 RFID 리더를 추가로 설치하였다. 제어부와, 작업의 시작과 종료 시 카드를 통과시키는 카드리더와, 산출된 머신 팩터와 맨 팩터를 PLC 통신포트, 직렬통신포트, 이더넷 통신포트 등을 거쳐 네트웍상의 서버로 전송할 수 있도록 하였다. 이에 따라, 본 연구는 생산원가나 정확한 생산효율을 실시간으로 산출할 수 있으므로 효과적인 생산관리가 가능하게 되어, 원가절감과 생산성 향상에 크게 기여할 수 있게 되었다.

In this paper, the implementation of a production control system has been studied in order to obtain Realtime Cost Calculation using an exact Machine Factor and Man Factor based on RFID reader data transferred through network. For the study, microprocessor built in the controller of production facilities is used and also RFID reader is built additionally. Control part, card reader used for check the beginning and ending working time of workers, and Machine Factor and Man Factor calculated are transferred to server via PLC transmission port, serial transmission port, or Ethernet transmission port. By using the system, the production cost or the production efficiency is calculated exactly. Therefore it is possible to improve production rate and cost reduction by the use of the proposed production control system.