• 대한산업공학회지
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• 제31권3호
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• pp.180-193
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• 2005

This paper deals with a multiobjective process planning problem of flexible assembly systems(FASs). The FAS planning problem addressed in this paper is an integrated one of the assignment of assembly tasks to stations and the determination of assembly routing, while satisfying precedence relations among the tasks and flexibility capacity for each station. In this research, we consider two objectives: minimizing transfer time of the products among stations and absolute deviation of workstation workload(ADWW). We place emphasis on finding a set of diverse near Pareto or true Pareto optimal solutions. To achieve this, we present a new multiobjective coevolutionary algorithm for the integrated problem here, named a multiobjective symbiotic evolutionary algorithm(MOSEA). The structure of the algorithm and the strategies of evolution are devised in this paper to enhance the search ability. Extensive computational experiments are carried out to demonstrate the performance of the proposed algorithm. The experimental results show that the proposed algorithm is a promising method for the integrated and multiobjective problem.

• Journal of Information Processing Systems
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• 제14권2호
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• pp.487-498
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• 2018

The purpose of the high-speed railway construction is to better satisfy passenger travel demands. Accordingly, the design of the train working plan must also take a full account of the interests of passengers. Aiming at problems, such as the complex transport organization and different speed trains coexisting, combined with the existing research on the train working plan optimization model, the multiobjective bi-level programming model of the high-speed railway passenger train working plan was established. This model considers the interests of passengers as the center and also takes into account the interests of railway transport enterprises. Specifically, passenger travel cost and travel time minimizations are both considered as the objectives of upper-level programming, whereas railway enterprise profit maximization is regarded as the objective of the lower-level programming. The model solution algorithm based on genetic algorithm was proposed. Through an example analysis, the feasibility and rationality of the model and algorithm were proved.

• Steel and Composite Structures
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• 제14권2호
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• pp.121-132
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• 2013

This paper deals with multiobjective optimization of symmetrically laminated composite angle-ply annular sector plates subjected to axial uniform pressure load and thermal load. The design objective is the maximization of the weighted sum of the critical buckling load and fundamental frequency. The design variable is the fibre orientations in the layers. The performance index is formulated as the weighted sum of individual objectives in order to obtain the optimum solutions of the design problem. The first-order shear deformation theory is used for the mathematical formulation. Finally, the effects of different weighting factors, annularity, sector angle and boundary conditions on the optimal design are investigated and the results are compared.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.691-700
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• 2007

This paper proposes a simple but effective design method of PID control using a numerical optimization method. In order to achieve both stability and performance, gain and phase margins and performance indices of step response directly compose of the cost function. Hence, the proposed approach is a multiobjective optimization problem. The main effectiveness of this approach results from the strong capability of the used optimization method. A one-dimensional example concerning gain margin illustrates the practical applicability of the optimization method. The present approach has many degrees of freedom in controller design by only adjusting related weight constants. The attained PID controller is compared with Wang#s and Ho#s methods, IAE, and ISE for a high-order process, and the simulation result for various design targets shows that the proposed approach achieves desired time-domain performance with a guarantee of frequency-domain stability.

• Journal of Advanced Marine Engineering and Technology
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• 제24권3호
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• pp.99-105
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• 2000

For multi-body dynamic problems. especially coalescent eigenvalue problems with multiobjective optimization, the design sensitivity analysis is too much complicated mathematically and numerically. Therefore, this article proposes a new technique for structural dynamic modification using a mode modification and homologous structures design method with Genetic Algorithm(GA). In this work, the homologous structure of the resiliently mounted multi-body for marine diesel generator systems is studied and the problem is treated as a combinational optimization problem using the GA. In GA formulation, fitness is defined based on penalty function approach. That include homology, allowable stress and minimum weight of common plate.

• Wind and Structures
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• 제34권3호
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• pp.259-274
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• 2022

The present paper is focused on analyzing a set of Computational Fluid Dynamics (CFD) simulation data on reducing orthogonal peak base moment coefficients on a high-rise rectangular building with wings. The study adopts an aerodynamic optimization procedure (AOP) composed of CFD, artificial neural network (ANN), and genetic algorithm (G.A.). A parametric study is primarily accomplished by altering the wing positions with 3D transient CFD analysis using k - ε turbulence models. The CFD technique is validated by taking up a wind tunnel test. The required design parameters are obtained at each design point and used for training ANN. The trained ANN models are used as surrogates to conduct optimization studies using G.A. Two single-objective optimizations are performed to minimize the peak base moment coefficients in the individual directions. An additional multiobjective optimization is implemented with the motivation of diminishing the two orthogonal peak base moments concurrently. Pareto-optimal solutions specifying the preferred building shapes are offered.

• 한국정밀공학회지
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• 제21권9호
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• pp.149-157
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• 2004

This paper presents a new method for hi-objective optimization. Ordinary weighted sum method is easy to implement, but it has two significant drawbacks: (1) the solution distribution by the weighted sum method is not uniform, and (2) the method cannot determine any solutions that reside in non-convex regions of a Pareto front. The proposed adaptive weighted sum method does not solve a multiobjective optimization in a predetermined way, but it focuses on the regions that need more refinement by imposing additional inequality constraints. It is demonstrated that the adaptive weighted sum method produces uniformly distributed solutions and finds solutions on non-convex regions. Two numerical examples and a simple structural problem are presented to verify the performance of the proposed method.

• Nuclear Engineering and Technology
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• 제42권4호
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• pp.414-425
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• 2010

In this paper, a procedure is developed for identifying a number of representative solutions manageable for decision-making in a multiobjective optimization problem concerning the test intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are identified by a genetic algorithm and then clustered by subtractive clustering into "families". On the basis of the decision maker's preferences, each family is then synthetically represented by a "head of the family" solution. This is done by introducing a scoring system that ranks the solutions with respect to the different objectives: a fuzzy preference assignment is employed to this purpose. Level Diagrams are then used to represent, analyze and interpret the Pareto Fronts reduced to the head-of-the-family solutions.

• 대한조선학회논문집
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• 제32권2호
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• pp.10-21
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• 1995

본 논문에서는 설계자에게 보다 많은 정보를 제공할 수 있는 다목적함수 최적화방법을 이용하여 선박의 주요치수를 최적화하였다. 최적화에서 운항비와 건조비가 경제성에 미치는 영향을 보다 상세히 분석하기 위하여, 건조비와 운항비를 각각의 목적함수로 하여 다목적함수 최적화를 수행하였고, RFR은 종속함수로 계산하여 변화경향을 분석하였다. 최적화를 위한 설계모델로는 운항거리가 비교적 긴 항로에 대하여, 선속이 빠르며 다른 선종에 비하여 건조비가 높은 액화천연가스 운반선을 대상으로 하였다.

• 한국통신학회논문지
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• 제32권11A호
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• pp.1079-1085
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• 2007

NSGA (Non-dominated Sorting Algorithm) 는 다목적 최적화 분야에서 널리 사용되고 있는 비지배 정렬 기반의 유전자 알고리즘으로 최적화를 요구하는 분야에서 널리 사용되고 있다. 하지만 연산의 복잡도, 사전 우수해 선별 조건의 미흡함과 공유 변수값 결정의 어려움등이 문제로 제기 되었고, 이러한 단점을 보완한 NSGA-II(Non-dominated Sorting Algorithm-B) 알고리즘이 제안되었다. 그러나 기존의 NSGA-II알고리즘은 다목적 최적화 알고리즘과 동일하게 목적치를 최대화 또는 최소화시키는 방향으로 최적화가 진행되어 선택적인 최적화 수행이 어렵다. 이러한 문제점을 보완하기 위하여 본 논문에서는 NSGA-II알고리즘이 가지는 장점을 바탕으로 설계자의 요구조건에 종속적으로 최적화 과정을 수행할 수 있는 GBNSGA-II (Goal-pareto Based NSGA-II)를 제안하고 기존의 NSGA-II알고리즘과 비교를 통해 성능의 우수성을 검증하였다.