• Industrial Engineering and Management Systems
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• v.10 no.3
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• pp.203-208
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• 2011

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.490-492
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• 1998

In this paper, fuzzy-PD control system is designed to control angle and position of the inverted pendulum. To optimize parameters of fuzzy-PD controller, we used adaptive evolutionary computation(AEC). AEC uses a Genetic A1gorithm(GA) and an Evolution Strategy(ES) in an adaptive manner in order to take merits of two different evolutionary computations.

• Journal of the Korean Society of Systems Engineering
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• v.3 no.1
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• pp.9-15
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• 2007

An EA(Evolutionary Acquisition) strategy is based on the systems engineering. It is a preferred approach to provide operationally useful capabilities to the warfighter much more quickly than single-step to full capability strategy. Recently, DoD is trying to apply the acquisition process based on the systems engineering. In spite of these trends, efforts of domestic defense acquisition society to this strategy are insufficient. Although an EA strategy has many benefits, there are many constraints to apply it. This study analyzes these constraints and presents applications of the EA strategy to defense R&D programs.

• Journal of Microbiology and Biotechnology
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• v.19 no.11
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• pp.1301-1305
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• 2009

The evolution of living organisms occurs via a combination of highly complicated processes that involve modification of various features such as appearance, metabolism and sensing systems. To understand the evolution of life, it is necessary to understand how each biological feature has been optimized in response to new environmental conditions and interrelated with other features through evolution. To accomplish this, we constructed contents-based trees for a two-component system (TCS) and metabolic network to determine how the environmental communication mechanism and the intracellular metabolism have evolved, respectively. We then conducted a comparative analysis of the two trees using ARACNE to evaluate the evolutionary and functional relationship between TCS and metabolism. The results showed that such integrated analysis can give new insight into the study of bacterial evolution.

• Genomics & Informatics
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• v.7 no.2
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• pp.111-121
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• 2009

Cell membrane proteins play crucial roles in the cell's molecular interaction with its environment and within itself. They consist of membrane-bound proteins and many types of transmembrane (TM) proteins such as receptors, transporters, channel proteins, and enzymes. Membrane proteomes of cellular organisms reveal some characteristics in their global topological distribution according to their evolutionary positions, and show their own information transfer complexity. Predicted transmembrane segments (TMSs) in membrane proteomes with HMMTOP showed near power-law distribution and frequency characteristics in 6-TMS and 7-TMS proteins in prokaryotes and eukaryotes, respectively. This reaffirms the important roles of membrane receptors in cellular communication and biological evolutionary history.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.305-308
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• 2007

In this paper we suggest an efficient evolutionary approach based on topological sort techniques for precedence constrained TSPs. The determination of optimal sequence has much to offer to downstream project management and opens up new opportunities for supply chains and logistics. Experimental results show that the suggested approach is a good alternative to locate optimal solution for complicated precedence constrained sequencing as in optimization method for instance.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2563-2569
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• 2024

The monochromatic hyperbolic neutron density wave is conceived as a Rayleigh-like wave with mixed transverse and longitudinal components. It is proved for the first time that the absolute ratio of the longitudinal to transverse interfering components, varies, with increasing the frequency of this wave, from zero to 1. Such a limited variation is to be coined as vibrational enhancement of evolutionary one-speed neutron transport.

• Structural Engineering and Mechanics
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• v.7 no.5
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• pp.447-456
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• 1999

This paper presents a solution method, which can be regarded as the further extension of the generalized evolutionary method (Zhao et al. 1998a), for the simultaneous optimization of several different natural frequencies of a structure in general and a two dimensional structure in particular. The main function of the present method is to optimize the topology of a structure so as to simultaneously make several different natural frequencies of interest to be of the corresponding different desired values for the target structure. In order to develop the present method, the new contribution factor of an element is proposed to consider the contribution of an element to the gaps between the currently calculated values for the different natural frequencies of interest and their corresponding desired values in a weighted manner. Using this new contribution factor of an element, the most inefficiently used material can be detected and removed gradually from the design domain of a structure. Through applying the present method to optimize two and three different natural frequencies of a two dimensional structure, it has been demonstrated that it is possible and applicable to use the generalized evolutionary method for tackling the simultaneous optimization of several different natural frequencies of a structure in the structural design.

• International Journal of Fluid Machinery and Systems
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• v.3 no.2
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• pp.150-159
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• 2010

Laidback fan shaped film-cooling hole is formulated numerically and optimized with the help of three-dimensional numerical analysis, surrogate methods, and the multi-objective evolutionary algorithm. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by four geometric design variables, the injection angle of the hole, the lateral expansion angle of the diffuser, the forward expansion angle of the hole, and the ratio of the length to the diameter of the hole, to maximize the film-cooling effectiveness compromising with the aerodynamic loss. The objective function values are numerically evaluated through Reynolds- averaged Navier-Stokes analysis at the designs that are selected through the Latin hypercube sampling method. Using these numerical simulation results, the Response Surface Approximation model are constructed for each objective function and a hybrid multi-objective evolutionary algorithm is applied to obtain the Pareto optimal front. The clustered points from Pareto optimal front were evaluated by flow analysis. These designs give enhanced objective function values in comparison with the experimental designs.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.4
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• pp.303-315
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• 2005

In this paper we address a design problem for hub-and-spoke networks and then consider a capacitated hub locations problem with direct shipment (CHLPwD). We determine the location of hubs, the allocation of nodes to hubs, and direct shipment paths in the network, with the objective of minimizing the total cost in the network. In this paper, CHLPwD is formulated as 0-1 integer programming. We develop an evolutionary algorithm here to solve the large sized CHLPwD. To do this, we present the representation and the genetic operators suitable for the problem and propose a heuristic method for the allocation of nodes to hubs. To enhance the search capability, problem-specific information is used in our evolutionary algorithm. The proposed algorithm is compared with the heuristic method in terms of solution quality and computation time. The experimental results show that our algorithm can provide better solutions than the heuristic.