• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.142-156
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• 2015

A new method for ship Inner Shell optimization, which is called Parametric Inner Shell Optimization Method (PISOM), is presented in this paper in order to improve both hull performance and design efficiency of transport ship. The foundation of PISOM is the parametric Inner Shell Plate (ISP) model, which is a fully-associative model driven by dimensions. A method to create parametric ISP model is proposed, including geometric primitives, geometric constraints, geometric constraint solving etc. The standard optimization procedure of ship ISP optimization based on parametric ISP model is put forward, and an efficient optimization approach for typical transport ship is developed based on this procedure. This approach takes the section area of ISP and the other dominant parameters as variables, while all the design requirements such as propeller immersion, fore bottom wave slap, bridge visibility, longitudinal strength etc, are made constraints. The optimization objective is maximum volume of cargo oil tanker/cargo hold, and the genetic algorithm is used to solve this optimization model. This method is applied to the optimization of a product oil tanker and a bulk carrier, and it is proved to be effective, highly efficient, and engineering practical.

• Structural Engineering and Mechanics
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• v.53 no.4
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• pp.833-845
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• 2015

Natural frequencies of the structural systems should be far away from the excitation frequency in order to avoid or reduce the destructive effects of dynamic loads on structures. To accomplish this goal, a structural optimization on size and shape has been performed considering frequency constraints. Such an optimization problem has highly nonlinear property. Thus, the quality of the solution is not independent of the optimization technique to be applied. This study presents the performance evaluation of the recently proposed meta-heuristic algorithm called Teaching Learning Based Optimization (TLBO) as an optimization engine in the weight optimization of the truss structures under frequency constraints. Some examples regarding the optimization of trusses on shape and size with frequency constraints are solved. Also, the results obtained are tabulated for comparison. The results demonstrated that the performance of the TLBO is satisfactory. Additionally, TLBO is better than other methods in some cases.

• Steel and Composite Structures
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• v.15 no.4
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• pp.451-466
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• 2013

This paper deals with the multi-objective optimization of tire reinforcement structures such as the tread belt and the carcass path. The multi-objective functions are defined in terms of the discrete-type design variables and approximated by artificial neutral network, and the sensitivity analyses of these functions are replaced with the iterative genetic evolution. The multi-objective optimization algorithm introduced in this paper is not only highly CPU-time-efficient but it can also be applicable to other multi-objective optimization problems in which the objective function, the design variables and the constraints are not continuous but discrete. Through the illustrative numerical experiments, the fiber-reinforced tire belt structure is optimally tailored. The proposed multi-objective optimization algorithm is not limited to the tire reinforcement structure, but it can be applicable to the generalized multi-objective structural optimization problems in various engineering applications.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.469-475
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• 2008

The design of a scramjet inlet is a process to search global optimization results among those factors influencing the geometry of scramjet in their ranges for some requirements. An optimization algorithm of hybrid genetic algorithm based on genetic algorithm and simplex algorithm was established for this purpose. With the sample provided by a uniform method, the compressive angles which also are wedge angles of the inlet were chosen as the inlet design variables, and the drag coefficient, total pressure recovery coefficient, pressure rising ratio and the combination of these three variables are designed specifically as different optimization objects. The contrasts of these four optimization results show that the hybrid genetic algorithm developed in this paper can capably implement the optimization process effectively for the inlet design and demonstrate some good adaptability.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.182-191
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• 2011

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.61-69
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• 2007

The objective of this work is to integrate reliability analysis into topology optimization problems. We introduce the reliability constraint in the topology optimization formulation, and the new model is called Reliability-Based Topology Optimization (RBTO). The application of the RBTO model gives a different topology relative to the classical topology optimization that should be deterministic. When comparing the structures resulting from the deterministic topology optimization and from the RBTO model, the RBTO model yields structures that are more reliable than the deterministic ones (for the same weight). Several applications show the importance of this integration.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.19-27
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• 2009

This paper presents a newly developed optimization algorithm, the Bee Optimization Algorithm (BeeOA), to solve the economic power dispatch (EPD) problem. The authors have developed a derivative free and global optimization technique based on the working of the honey bee. The economic power dispatch problem is a nonlinear constrained optimization problem. Classical optimization techniques fail to provide a global solution and evolutionary algorithms provide only a good enough solution. The proposed approach has been examined and tested on two test systems with different objectives. A simple power dispatch problem is tested first on 6 generators and then the algorithm is demonstrated on 13 thermal unit systems whose incremental fuel cost function takes into account the value point loading effect. The results are promising and show the effectiveness and robustness of the proposed approach over recently reported methods.

• Management Science and Financial Engineering
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• v.21 no.2
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• pp.1-8
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• 2015

This paper gives a brief review of the theory and applications of the robust optimization. Major issues including tractability, relations with relevant optimization frameworks, and dynamic robust optimization are addressed and future research directions are presented.

• 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.

• 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.