• International Journal of Aeronautical and Space Sciences
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• 제17권2호
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• pp.268-283
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• 2016

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

• Journal of Advanced Marine Engineering and Technology
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• 제23권4호
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• pp.574-582
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• 1999

This paper discusses the multi-level optimization method in dynamic optimization problems through stiffened plate of ship structures. In structural optimization the computational cost increases rapidly as the number of design variables increases. And we need a great amount of cal-culation and time on problems of modified dynamic characteristics of large and complicated struc-tures. In this paper the multi-level optimization is proposed which decreases computational time and cost. the dynamic optimum designs of stiffened plate that control the natural frequency and minimize weight subjected to constraints condition are derived. The way to apply the multi-level optimization methods in this study follow: In the first step the dynamic characteristics is controlled for the two-dimensional model of stiffened plate by sensitivity analysis and quasi-least squares methods. In the second step the cross-section of the stiffener is decided so that the weight is minimized under needed constraints by the steepest descent or ascent method. In the third the three-dimensional model is made based on the results of the first step and the second step confirmation and finer tuning of the objective function are carried out. It is shown that the results are effective in the optimum modification for dynamic characteristics of the stiffened plate.

• 설비공학논문집
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• 제12권11호
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• pp.982-993
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• 2000

This paper describes an optimal control scheduling of an encapsulated ice storage system with a chiller of nominal chiller 34RT(103,200kcal/hr) and an ice storage tank of 170RT-hrs(514,080 kcal). The optimization technique used in the study is dynamic programing. The objective function is summed cost during a day including charge and discharge periods. Control strategies being used commercially are chiller priority and storage priority control. In chiller priority control, the chiller is allowed to run at full capacity during the day, subject to limitations of the building load, and the ice is only melted when and if the load exceeds the chillers full capacity. In contrast to chiller priority control, the aim in storage priority control is to melt as much as ice as possible during the day time period. The system simulation calculates the operation costs for the three control strategies in the condition of the same cooling load and the same ice storage system. The simulation period is a day, assuming that initially the tank is stored fully and the cooling load is perfectly predicted for the scheduling. Also Final state of the tank is to be charged fully.

• 전기학회논문지
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• 제60권4호
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• pp.717-725
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• 2011

In the power system with an electric storage system that can increase utilization rate of the source of such new renewable energy, this paper introduces the approach on the daily unit commitment scheduling that determines simultaneously optimum operational condition and output of thermal generators and electric storage device. The unit commitment is one of the most important issues in economic operation and security of short-term operational plan of the power system. It is to determine on/off status of generator to minimize operational cost during the given period. The committed generator should satisfy various operational limitation such as estimated demand by system, spinning reserve condition within minimum operational cost. In order to determine on/off or charge/discharge/idle condition and output level of units and electric storage system, the MILP(Mixed Integer Linear Programming) is suggested. The proposed approach is the mixed method between LP(Linear Programming) and IP(integer programming) which seeks the value of real number and integer that maximize or minimize function objective within given condition. The daily unit commitment problem with the electric storage system is applied to MILP algorithm through linearization and formulation process. The proposed approach is applied to the test system.

• Geomechanics and Engineering
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• 제24권3호
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• pp.237-251
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• 2021

The main purpose of this study is to investigate the performance of the proposed hybrid teaching-learning based optimization algorithm on the optimum design of reinforced concrete (RC) cantilever retaining walls. For this purpose, three different design examples are optimized with 100 independent runs considering continuous and discrete variables. In order to determine the algorithm performance, the optimization results were compared with the outcomes of the nine powerful meta-heuristic algorithms applied to this problem, previously: the big bang-big crunch (BB-BC), the biogeography based optimization (BBO), the flower pollination (FPA), the grey wolf optimization (GWO), the harmony search (HS), the particle swarm optimization (PSO), the teaching-learning based optimization (TLBO), the jaya (JA), and Rao-3 algorithms. Moreover, Rao-1 and Rao-2 algorithms are applied to this design problem for the first time. The objective function is defined as minimizing the total material and labor costs including concrete, steel, and formwork per unit length of the cantilever retaining walls subjected to the requirements of the American Concrete Institute (ACI 318-05). Furthermore, the effects of peak ground acceleration value on minimum total cost is investigated using various stem height, surcharge loads, and backfill slope angle. Finally, the most robust results were obtained by HTLBO with 50 populations. Consequently the optimization results show that, depending on the increase in PGA value, the optimum cost of RC cantilever retaining walls increases smoothly with the stem height but increases rapidly with the surcharge loads and backfill slope angle.

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.69-78
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• 2007

In real world, the project managers handle conflicting goals that govern the use of resources within the stipulated time and budget with required quality and safety. These conflicting goals are required to be optimized simultaneously by the project managers in the framework of fuzzy aspiration levels. The fuzzy linear programming model proposed herein helps project managers to minimize total project costs, completion time, and crashing costs considering indirect costs, contractual penalty costs etc by practically charging them in terms of direct cost of the project. A case study of bituminous pavement under construction is considered to demonstrate the feasibility of applying the proposed model for optimization of project parameters. Consequently, the proposed model yields an efficient compromise solution and the decision maker's overall degree of satisfaction with multiple fuzzy goal values. Additionally, the proposed model provides a systematic decision-making framework, enabling decision maker to interactively modify the fuzzy data and model parameters until a satisfactory solution is obtained. The significant characteristics that differentiate the proposed model with other models include, flexible decision-making process, multiple objective functions, and wide-ranging decision information.

• Steel and Composite Structures
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• 제44권5호
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• pp.603-617
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• 2022

Structural design, in general, is developed through trial and error technique which is guided by standards criteria and based on the intuition and experience of the engineer, a context that leads to structural over-dimensioning, with uneconomic solutions. Aiming to find the optimal design, structural optimization methods have been developed to find a balance between cost, structural safety, and material performance. These methods have become a great opportunity in the steel structural engineering domain since they have as their main purpose is weight minimization, a factor directly correlated to the real cost of the structure. Assuming an objective function of minimum weight with stress and displacement constraints provided by Brazilian standards, the present research proposes the sizing optimization and combined approach of sizing and shape optimization, through a software developed to implement the Simulated Annealing metaheuristic algorithm. Therefore, two steel plane frame layouts, each admitting four typical truss geometries, were proposed in order to expose the difference between the optimal solutions. The assessment of the optimal solutions indicates a notable weight reduction, especially in sizing and shape optimization combination, in which the quantity of design variables is increased along with the search space, improving the efficiency of the optimal solutions achieved.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1626-1634
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• 2015

LCL filters are widely used in three-phase PWM converter for its advantages of small volume, low cost and inhibition of high frequency current harmonic. However, it is difficult to optimize its design because its parameters are mutually influenced while the value of each parameter for LCL filter has impacts on the converter's cost and size. In this paper, the target of optimization is to minimize the parameter values of LCL filter, and an optimization method for parameters of LCL filter of three-phase PWM converter based on least square method is proposed. With this method, a quantitative calculation of the harmonic component of the converter’s side phase voltage is performed first, and then the quantitative relationship between phase voltage harmonics and grid phase current harmonics is analyzed. After that, the attenuation requirement of each harmonic is obtained by taking into account the requirements for each harmonic component of grid current. Then according to the optimization objective, the objective function with minimum harmonic attenuation deviation is established, and least squares method is adopted for three-dimensional global searching of parameters for LCL filter. Thus, the designed harmonic attenuation curve approximates the minimum attenuation requirements, and the optimized LCL filter parameters are obtained. Finally, the effectiveness of the method is verified by the experiments.

• 대한교통학회지
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• 제22권3호
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• pp.167-177
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• 2004

Hub-and-spoke운송은 교통분야에서 널리 이용되고 있는 운송전략의 대표적 개념이다. 화물의 컨테이너화와 환적기술의 발달로 최근 유럽을 중심으로 철도화물운송부문에서도 이 운송전략의 적용사례가 나타나고 있다. 이에 본 연구는 Hub-and-spoke운송전략을 구현하는 철도화물서비스네트워크 디자인모형을 제시하고, 대규모 운송망에도 적용이 가능한 효율적 알고리즘을 개발하였다. 개발되는 모형이 전략적 수준의 계획모형임에도 불구하고 모형에서는 일반화된 운영비용 외에 열차속도, 서비스빈도, 터미널에서의 화물처리속도 등에 따른 시간지체비용도 고려되었다. 시간지체비용의 고려에 따라 야기되는 목적함수의 비선형성은 빈도별 서비스결정변수의 설정을 통해 선형최적화문제로 표현되었다. 규모가 큰 네트워크의 경우 해도출의 어려움 때문에 본 논문은 전체문제의 분할(decomposition)에 기초한 휴리스틱방법((heuristic method)으로 문제를 해결하고자 하였다. 해도출의 효율성을 높이기 위해 서비스빈도개선과 관련하여 3개의 알고리즘이 개발되었고, 개발된 알고리즘은 유럽의 실제네트워크를 기초로 도출한 4개의 테스트문제를 대상으로 해의 정확도와 해 도출의 효율성이 비교 평가되었다.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1508-1517
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• 2015

Optimal Power dispatch is the short-term decision of the optimal output of a number of power generation facilities, to meet the system demand, with the objective of Power dispatching at the lowest possible cost, subject to transmission lines power loss and operational constraints. The operational constraint includes power balance constraint, generator limit constraint, and emission dispatch constraint and valve point effects. In this paper, Opposition based Differential Evolution Algorithm (ODEA) has been proposed to handle the objective function and the operational constraints simultaneously. Furthermore, the valve point loading effects and transmission lines power loss are also considered for the efficient and effective Power dispatch. The ODEA has unique features such as self tuning of its control parameters, self acceleration and migration for searching. As a result, it requires very minimum executions compared with other searching strategies. The effectiveness of the algorithm has been validated through four standard test cases and compared with previous studies. The proposed method out performs the previous methods.