• 한국생산제조학회지
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• 제19권4호
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• pp.469-475
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• 2010

The objective of this study is to integrate reliability analysis into shape optimization problem using the evolutionary structural optimization (ESO) in the application example. Reliability-based shape optimization is formulated as volume minimization problem with probabilistic stress constraint under minimization max. von Mises stress and allow stress. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., reliability index approach (RIA), performance measure approach (PMA), single-loop singlevector (SLSV) and adaptive-loop (ADL), are used. Reliability-based shape optimization design process is conducted to obtain optimal shape satisfying max. von Mises stress and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.

• 한국음향학회지
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• 제32권3호
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• pp.237-246
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• 2013

본 논문에서는 캐비테이션 터널에서의 소음계측용 청음기 배열 설계를 위한 최적화 기법을 제안하였다. 제안된 최적설계 기법은 배열 설계인자 및 목적함수 정의 그리고 최적화 알고리즘 적용 등의 내용으로 구성되어 있다. 설계인자 정의는 원형배열, 나선배열, 다중나선배열을 대상으로 하였다. 목적함수는 주엽의 빔폭과 최대 부엽 크기를 동시에 고려할 수 있도록 정의하였다. 최적화 알고리즘으로는 광역 최적화 기법의 일종인 VFSR 기법을 적용하였다. 최적 설계기법을 각 배열에 적용 후 도출된 최적 배열을 대상으로 최대 부엽크기 및 주엽의 빔폭을 분석하였다. 끝으로 캐비테이션 터널 내부의 다중반사를 고려한 빔형성 결과 평가를 통해 본 기법의 유용성을 확인하였다.

• Journal of Communications and Networks
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• 제14권1호
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• pp.91-103
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• 2012

Network mobility (NEMO) based on mobile IP version 6 has been proposed for networks that move as a whole. Route optimization is one of the most important topics in the field of NEMO. The current NEMO basic support protocol defines only the basic working mode for NEMO, and the route optimization problem is not mentioned. Some optimization schemes have been proposed in recent years, but they have limitations. A new NEMO route optimization scheme-involving a combination of the optimized route cache protocol (ORC) and reverse routing header (RRH) and the use of a quota mechanism for optimized sessions (OwR)-is proposed. This scheme focuses on balanced performance in different aspects. It combines the ORC and RRH schemes, and some improvements are made in the session selection mechanism to avoid blindness during route optimization. Simulation results for OwR show great similarity with those for ORC and RRH. Generally speaking, the OwR's performance is at least as good as that of the RRH, and besides, the OwR scheme is capable of setting up optimal routing for a certain number of sessions, so the performance can be improved and the cost of optimal routing in nested NEMO can be decreased.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.1821-1830
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• 2018

With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important component of home-based intelligent electricity. In this study, a multi-objective optimization model in an intelligent electricity environment is proposed based on economy and comfort. Firstly, the domestic consumer's load characteristics are analyzed, and the operating constraints of interruptible and transferable electrical appliances are defined. Then, constraints such as household electrical load, electricity habits, the correlation minimization electricity expenditure model of household appliances, and the comfort model of electricity use are integrated into multi-objective optimization. Finally, a continuous search multi-objective particle swarm algorithm is proposed to solve the optimization problem. The analysis of the corresponding example shows that the multi-objective optimization model can effectively reduce electricity costs and improve electricity use comfort.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권5호
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• pp.1951-1972
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• 2018

Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

• Smart Structures and Systems
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• 제25권3호
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• pp.345-368
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• 2020

The present work proposes a self-controlled multi-stage optimization method for damage identification of structures utilizing standard particle swarm optimization (PSO) algorithm. Damage identification problem is formulated as an inverse optimization problem where damage severity in each element of the structure is considered as optimization variables. An efficient objective function is formed using the first few frequencies and mode shapes of the structure. This objective function is minimized by a self-controlled multi-stage strategy to identify and quantify the damage extent of the structural members. In the first stage, standard PSO is utilized to get an initial solution to the problem. Subsequently, the algorithm identifies the most damage-prone elements of the structure using an adaptable threshold value of damage severity. These identified elements are included in the search space of the standard PSO at the next stage. Thus, the algorithm reduces the dimension of the search space and subsequently increases the accuracy of damage prediction with a considerable reduction in computational cost. The efficiency of the proposed method is investigated and compared with available results through three numerical examples considering both with and without noise. The obtained results demonstrate the accuracy of the present method can accurately estimate the location and severity of multi-damage cases in the structural systems with less computational cost.

• Structural Engineering and Mechanics
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• 제59권5호
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• pp.933-950
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• 2016

Decks, interior beams, edge beams and girders are the parts of a steel floor system. If the deck is optimized without considering beam optimization, finding best result is simple. However, a deck with higher cost may increase the composite action of the beams and decrease the beam cost reducing the total cost. Also different number of floor divisions can improve the total floor cost. Increasing beam capacity by using castellated beams is other efficient method to save the costs. In this study, floor optimization is performed and these three issues are discussed. Floor division number and deck sections are some of the variables. Also for each beam, profile section of the beam, beam cutting depth, cutting angle, spacing between holes and number of filled holes at the ends of castellated beams are other variables. Constraints include the application of stress, stability, deflection and vibration limitations according to the load and resistance factor (LRFD) design. Objective function is the total cost of the floor consisting of the steel profile cost, cutting and welding cost, concrete cost, steel deck cost, shear stud cost and construction costs. Optimization is performed by enhanced colliding body optimization (ECBO), Results show that using castellated beams, selecting a deck with higher price and considering different number of floor divisions can decrease the total cost of the floor.

• Nuclear Engineering and Technology
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• 제52권5호
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• pp.956-963
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• 2020

Dose optimization for Radioactive Occupational Personal (ROP) is an important subject in nuclear and radiation safety field. The geometric environment of a nuclear facility is complex and the work area is radioactive, so traditional navigation model and radioactive data field cannot form an effective environment model for dose assessment and dose optimization. The environment model directly affects dose assessment and indirectly affects dose optimization, this is an urgent problem needed to be solved. Therefore, this paper focuses on an environment model used for Dose Assessment and Dose Optimization (DA&DO). We designed a multi-layer radiation field coupling modeling method, and then explored the influence of the environment model to DA&DO by virtual simulation. Then, a simulation test is done, the multi-layer radiation field coupling model for nuclear facilities is demonstrated to be effective for dose assessment and dose optimization through the experiments and analysis.

• Advances in aircraft and spacecraft science
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• 제4권3호
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• pp.297-316
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• 2017

With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.