• International Journal of Naval Architecture and Ocean Engineering
• /
• 제6권2호
• /
• pp.406-417
• /
• 2014

This paper presents a numerical optimization method to improve the performance of the propeller with Turbo-Ring using real-coded genetic algorithm. In the presented method, Unimodal Normal Distribution Crossover (UNDX) and Minimal Generation Gap (MGG) model are used as crossover operator and generation-alternation model, respectively. Propeller characteristics are evaluated by a simple surface panel method "SQCM" in the optimization process. Blade sections of the original Turbo-Ring and propeller are replaced by the NACA66 a = 0.8 section. However, original chord, skew, rake and maximum blade thickness distributions in the radial direction are unchanged. Pitch and maximum camber distributions in the radial direction are selected as the design variables. Optimization is conducted to maximize the efficiency of the propeller with Turbo-Ring. The experimental result shows that the efficiency of the optimized propeller with Turbo-Ring is higher than that of the original propeller with Turbo-Ring.

• 한국항해항만학회지
• /
• 제33권9호
• /
• pp.635-644
• /
• 2009

The optimum design of power yacht belongs to the nonlinear constrained optimization problems. The determination of scantlings for the bow structure is a very important issue with in the whole structural design process. The derived design results are obtained by the use of real-coded micro-genetic algorithm including evaluation from Lloyd's Register small craft guideline, so that the nominal limiting stress requirement can be satisfied. In this study, the minimum volume design of bow structure on the power yacht was carried out based on the finite element analysis. The target model for optimum design and local structural analysis is the bow structure of a power yacht. The volume of bow structure and the main dimensions of structural members are chosen as an objective function and design variable, respectively. During optimization procedure, finite element analysis was performed to determine the constraint parameters at each iteration step of the optimization loop. optimization results were compared with a pre-existing design and it was possible to reduce approximately 19 percents of the total steel volume of bow structure from the previous design for the power yacht.

• 조명전기설비학회논문지
• /
• 제18권6호
• /
• pp.55-62
• /
• 2004

산업공정에 가장 많이 활용되고 있는 일차 시지연 공정은 긴 지연시간으로 인하여 정확한 공정모델을 구하기 어려울 뿐만 아니라,플랜트와 모델불일치에 따른 제어성능에 문제가 발생할 수 있다. 따라서 일차 시지연 공정의 제어 문제에 있어서 기본적으로 공정의 정확한 모델을 구하기 위한 공정 파라메타 식별이 아주 중요하다. 본 논문에서는 지금까지 제안된 계단입력 시험에 의한 공정식별법보다 더 효율적인 실수형 유전알고리즘에 의한 공정식별법을 제안하였다. 또한, 이러한 추정전략은 다양한 사례를 통하여 유용한 결과를 얻었다.

• Journal of Biosystems Engineering
• /
• 제38권2호
• /
• pp.149-162
• /
• 2013

Purpose: In image segmentation via thresholding, Otsu and Kapur methods have been widely used because of their effectiveness and robustness. However, computational complexity of these methods grows exponentially as the number of thresholds increases due to the exhaustive search characteristics. Methods: Particle swarm optimization (PSO) and genetic algorithms (GAs) can accelerate the computation. Both methods, however, also have some drawbacks including slow convergence and ease of being trapped in a local optimum instead of a global optimum. To overcome these difficulties, we proposed two new multi-level thresholding methods based on Bacteria Foraging PSO (BFPSO) and real-coded GA algorithms for fast segmentation. Results: The results from BFPSO and real-coded GA methods were compared with each other and also compared with the results obtained from the Otsu and Kapur methods. Conclusions: The proposed methods were computationally efficient and showed the excellent accuracy and stability. Results of the proposed methods were demonstrated using four real images.

• International Journal of Aeronautical and Space Sciences
• /
• 제14권4호
• /
• pp.341-349
• /
• 2013

This paper considers the optimum design of flexbeam cross-sections for a full-scale bearingless helicopter rotor, using an efficient hybrid optimization algorithm based on particle swarm optimization, and an improved genetic algorithm, with an effective constraint handling scheme for constrained nonlinear optimization. The basic operators of the genetic algorithm, of crossover and mutation, are revisited, and a new rank-based multi-parent crossover operator is utilized. The rank-based crossover operator simultaneously enhances both the local, and the global exploration. The benchmark results demonstrate remarkable improvements, in terms of efficiency and robustness, as compared to other state-of-the-art algorithms. The developed algorithm is adopted for two baseline flexbeam section designs, and optimum cross-section configurations are obtained with less function evaluations, and less computation time.

• 제어로봇시스템학회논문지
• /
• 제9권2호
• /
• pp.168-175
• /
• 2003

A new algorithm based on Genetic Algorithms is proposed f3r solving process optimization problems formulated in MINLP, GDP and hybrid MINLP/GDP. This work is focused especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is experimented and many heuristics are adopted. Real and binary coded Genetic Algorithm initiates the global search in the entire search space and at every stage Simulated Annealing makes the candidates to climb up the local hills. Multi-Niche Crowding method is adopted as the multimodal function optimization technique. and the adaptation of probabilistic parameters and dynamic penalty systems are also implemented. New strategies to take the logical variables and constraints into consideration are proposed, as well. Various test problems selected from many fields of process systems engineering are tried and satisfactory results are obtained.

• 한국항공우주학회지
• /
• 제44권11호
• /
• pp.989-996
• /
• 2016

본 연구는 비선형 응답모델과 실수기반의 혼합형 유전자 알고리즘을 적용하여 로터의 트?-발란스(RTB) 기법을 개발하는 데 목적이 있다. 트?-발란스 조절 파라미터의 변화에 따른 트림해석 결과를 이용하여 2차의 근사함수를 이용하는 비선형 응답모델을 개발하였다. 트?편차와 기체의 진동응답을 최소화하기 위해 균형추 무게, 트림 탭(Trim Tab) 및 피치링크 길이를 최적화하기 위한 비선형계획 문제를 정식화하였다. 정식화 결과는 수렴성 향상을 위해 군집최적화 기법을 실변수기반의 유전자 알고리즘에 통합한 혼합형 유전자 기법을 사용함으로써 효율적인 해석이 가능하였다. 비선형 모델을 이용한 본 연구의 방법을 선형모델의 결과와 비교하여 본 연구의 방법을 검증하였으며 비선형모델을 사용하는 경우 선형모델의 결과보다 향상된 응답특성을 계산할 수 있음을 밝혔다.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 2004년도 추계학술대회
• /
• pp.111-116
• /
• 2004

이 논문에서는 모델조정기법과 실수코딩 유전알고리즘을 이용하여 주어진 직류모터 시스템의 파라미터를 추정하였다. 종래에 논 Ziegler- Nichols(Z-N)동조법, Cohen-Coon(C-C)동조법, IMC(Internal model control)동조법, Lopez ITAE(L-ITAE)동조법과 같이 경험적이고 실험적인 많은 방법들이 제안되었다. 본 논문에서는 실수코딩 유전알고리즘을 이용하여 PID 제어기의 파라미터들을 동조하는 방법을 제안하고 시뮬레이션과 실험을 통해 제안한 제어기의 성능을 증명하였다.

• 전기학회논문지
• /
• 제58권4호
• /
• pp.832-839
• /
• 2009

In this paper, we introduce an design of fuzzy relation-based fuzzy neural networks with multi-output. Fuzzy relation-based fuzzy neural networks comprise the network structure generated by dividing the entire input space. The premise part of the fuzzy rules of the network reflects the relation of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions such as constant, linear, and modified quadratic. For the multi-output structure the neurons in the output layer were connected with connection weights. The learning of fuzzy neural networks is realized by adjusting connections of the neurons both in the consequent part of the fuzzy rules and in the output layer, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, learning rate and momentum coefficient are automatically optimized by using real-coded genetic algorithm. Two examples are included to evaluate the performance of the proposed network.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
• /
• pp.652-658
• /
• 1998

We introduce the concept of a bi-population scheme for real-coded GAs consisting of an explorer sub-Ga and an exploiter sub-GA. The explorer sub-GA mainly performs global exploration of the search space, and incorporates a restart mechanism to help avoid being trapped at local optima. The exploiter sub-GA performs exploitation of fit local areas of the search space around the neighborhood of the best-so-far solution. Thus the search function of the algorithm is divided. the proposed technique exhibits performance significantly superior to standard GAs on two complex highly multimodal problems.