• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.1-7
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• 2019

It is one of the known methods to obtain the optimal solution using the Ant Colony Optimization Algorithm for the Traveling Salesman Problem (TSP), which is a combination optimization problem. In this paper, we solve the TSP problem by proposing an improved new ant colony optimization algorithm that combines genetic algorithm mutations in existing ant colony optimization algorithms to solve TSP problems in many cities. The new ant colony optimization algorithm provides the opportunity to move easily fall on the issue of developing local optimum values of the existing ant colony optimization algorithm to global optimum value through a new path through mutation. The new path will update the pheromone through an ant colony optimization algorithm. The renewed new pheromone serves to derive the global optimal value from what could have fallen to the local optimal value. Experimental results show that the existing algorithms and the new algorithms are superior to those of existing algorithms in the search for optimum values of newly improved algorithms.

• International Journal of Quality Innovation
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• v.5 no.1
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• pp.43-51
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• 2004

During process design or process optimization, it is quite common for experimenters to find optimum operating conditions for several responses simultaneously. The traditional multiresponse surfaces optimization methods do not consider the uncertain relationship among these responses sufficiently. For this reason, the authors propose an optimization method based on evidential reasoning theory by Dempster and Shafer. By maximizing the basic probability assignment function, which indicates the degree of belief that certain operating condition is the solution of this multiresponse surfaces optimization problem, the desirable operating condition can be found.

• Journal of Ocean Engineering and Technology
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• v.16 no.3
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• pp.28-33
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• 2002

Optimization of marine propellers of constant pitch is studied, with the help of the infinite dimensional optimization (Jang and Kinoshita, 2000a), which is based on the Hilbert space theory. As a numerical example, the MAU type propeller is considered and used as he initial guess for the optimization method. The numerical computations for an optimal marine propeller are performed for the constant pitch distribution. In addition, a new optimization is suggested with the constraint of constant pitch during optimization.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1600-1604
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• 2010

This paper presents the optimum design of the brushless motor to maximize the output power per weight considering the design parameter tolerance. The optimization is proceeded by commercial software that is adopted the scatter-search algorithm and the characteristic analysis is conducted by FEM. The stochastic optimum design results are compared with those of the deterministic optimization method. We can verify that the results of the stochastic optimization is superior than that of deterministic optimization.

• Structural Engineering and Mechanics
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• v.47 no.2
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• pp.209-225
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• 2013

A procedure employing a Teaching-Learning Based Optimization (TLBO) method is developed to design discrete pin jointed structures. TLBO process consists of two parts: the first part represents learning from teacher and the second part illustrates learning by interaction among the learners. The results are compared with those obtained using other various evolutionary optimization methods considering the best solution, average solution, and computational effort. Consequently, the TLBO algorithm works effectively and demonstrates remarkable performance for the optimization of engineering design applications.

• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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• pp.187-190
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• 2005

In this study, the reliablility based design optimization is peformed for an aircraft wing. The flexiblility of the wing was assumed by considering the interaction modeled by static aeroelasticity between aerodynamic forces and the structure. For a multidisciplinary design optimization the results of aerodynamic analysis and structural analysis were included in the optimization formulation. The First Order Reliability Method(FORM) was employed to consider the uncertainty of the designed points.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1079-1082
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• 2000

인터넷에서 호스트의 이동성을 지원해주기 위한 프로토콜인 Mobile IP 의 가장 근 문제점의 하나는 Triangle Routing Problem이며 이를 해결하기 위한 방안으로서 Route Optimization이 있다. 그러나, 이 방식은 Route Optimization 을 위해서 기존의 인터넷 호스트, 즉 Correspondent Node 가 Binding Cache를 유지하고, Encapsulation의 기능을 가져야 하고, Home Agent와 Security Association을 갖도록 변경이 불가피하다. 본 논문에서는 기존 인터넷 호스트에서의 변경을 필요로 하지 않는 새로운 Route Optimization 방안인 Backward-Compatible Route Optimization을 제시한다.

• Steel and Composite Structures
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• v.12 no.6
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• pp.541-548
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• 2012

This paper deals with the applicability of extended layerwise optimization method (ELOM) for frequency optimization of laminated composite plates. The design objective is the maximization of the fundamental frequency of the laminated plates. The fibre orientations in the layers are considered as design variables. The first order shear deformation theory (FSDT) is used for the finite element solution of the laminates. Finally, the numerical analysis is carried out to show the applicability of extended layerwise optimization algorithm of laminated plates for different parameters such as plate aspect ratios and boundary conditions.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.83-84
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• 2020

Sum Utility를 최적화하는 Convex Optimization Algorithm을 제안한다. 일반적으로, Sum Utility 최적화 문제는 Non Convex Optimization Problem이다. 하지만, '상대간섭'과 '간섭주요화'를 활용하여 Non Convex Optimization Problem이 간섭구간에 따라 Convex Optimization으로 해결할 수 있음을 확인하였다. 특히, 유틸리티 함수는 상대간섭 0.1 이하에서는 오목함수임을 확인하였다. 실험결과 상대간섭이 작아질수록 제안하는 알고리즘에 의한 Sum Utility는 증가함을 확인하였다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.341-345
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• 2003

This study develops modeling processes for alignment optimization considering characteristics of intersections using genetic algorithms and GIS for road alignment optimization. Since existing highway alignment optimization models have neglected the characteristics of intersections, they have shown serious weaknesses for real applications. In this paper, intersection costs include earthwork, right-of-way, pavement, accident, delay and fuel consumption costs that are sensitive and dominating to alignments. Also, local optimization of intersections for saving good alignment alternatives is developed and embedded. A highway alignment is described by parametric representation in space and vector manipulation is used to find the coordinates of intersections and other interesting points. The developed intersection cost estimation model is sufficiently precise for estimating intersection costs and eventually enhancing the performance of highway alignment optimization models. Also, local optimization of intersections can be used for improving search flexibility, thus allowing more effective intersections. It also provides a basis for extending the alignment optimization from single highways to networks. The presented two artificial examples show that the total intersection costs are substantial and sensitive to highway alignments.