• Journal of the Korean Operations Research and Management Science Society
• /
• v.32 no.4
• /
• pp.1-18
• /
• 2007

In this paper, we develop an adaptive genetic algorithm (aGA). The aGA has an adaptive scheme which can automatically determine the use of local search technique and adaptively regulate the rates of crossover and mutation operations during its search process. For the adaptive scheme, the ratio of degree of dispersion resulting from the various fitness values of the populations at continuous two generations is considered. For the local search technique, an improved iterative hill climbing method is used and incorporated into genetic algorithm (GA) loop. In order to demonstrate the efficiency of the aGA, i) a canonical GA without any adaptive scheme and ii) several conventional aGAs with various adaptive schemes are also presented. These algorithms, including the aGA, are tested and analyzed each other using various test problems. Numerical results by various measures of performance show that the proposed aGA outperforms the conventional algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.1
• /
• pp.40-45
• /
• 2008

This paper presents an optimal design of a permanent magnet actuator(PMA) using a parallel genetic algorithm. Dynamic characteristics of permanent magnet actuator model are analyzed by coupled electromagnetic-mechanical finite element method. Dynamic characteristics of PMA such as holding force, operating time, and peak current are obtained by no load test and compared with the analyzed results by coupled finite element method. The permanent magnet actuator model is optimized using a parallel genetic algorithm. Some design parameters of vertical length of permanent magnet, horizontal length of plunger, and depth of permanent magnet actuator are predefined for an optimal design of permanent magnet actuator model. Furthermore dynamic characteristics of the optimized permanent magnet actuator model are analyzed by coupled finite element method. A displacement of plunger, flowing current of the coil, force of plunger, and velocity of plunger of the optimized permanent magnet actuator model are compared with the results of a primary permanent magnet actuator model.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.24 no.3
• /
• pp.27-37
• /
• 1999

In just-in-time production systems, U-shaped production lines rather than traditional straight lines are often adopted since they have some advantages. The advantages of U-lines over straight lines are that the workstations required can be reduced and the necessary number of workers can be easily adjusted when the demand rates are changed. In this paper, we present a new heuristic based on genetic algorithm to improve the workload smoothness in the U-line. In the proposed algorithm, a new genetic representation is developed which is specific to the problem being solved. To enhance the capability of searching good solutions, genetic operators are designed by using the problem-specific information and heuristics. Extensive experiments are carried out on well-known test-bed problems in the literature to verify the performance of our algorithm. The computational results show that our algorithm is a promising alternative to existing heuristics.

• Korean Management Science Review
• /
• v.14 no.2
• /
• pp.47-61
• /
• 1997

This paper considers the parallel machines scheduling problem characterized as a multi-objective combinatorial problem. As this problem belongs to the NP-complete problem, genetic algorithms are applied instead of the traditional analytical approach. The purpose of this study is to show how the problem can be effectively solved by using genetic algorithms with a permutation approach. First, a permutation representation which can effectively represent the chromosome is introduced for this problem . Next, a schedule builder which employs the combination of scheduling theories and a simple heuristic approach is suggested. Finally, through the computer experiments of genetic algorithm to test problems, we show that the niche formation method does not contribute to getting better solutions and that the PMX crossover operator is the best among the selected four recombination operators at least for our problem in terms of both the performance of the solution and the operational convenience.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.21 no.1
• /
• pp.111-117
• /
• 2007

This paper presents a new approach to evaluate reliability indices of electric distribution systems using genetic Algorithm (GA). The use of reliability evaluation is an important aspect of distribution system planning and operation to adjust the reliability level of each area. In this paper, the reliability model is based on the optimal load transforming problem to minimize load generated load point outage in each sub-section. This approach is one of the most difficult procedures and become combination problems. A new approach using GA was developed for this problem. GA is a general purpose optimization technique based on principles inspired from the biological evolution using metaphors of mechanisms such as natural selection, genetic recombination and survival of the fittest. Test results for the model system with 24 nodes 29 branches are reported in the paper.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.2
• /
• pp.355-360
• /
• 2005

This paper proposes bridge diagnosis system using Embedded LINUX and Genetic algorithm. The proposed system consists of MPC860 processor, FPCA, Bridge sensors and Genetic algorithm for bridge diagnosis. And the proposed system can operate with World Wide Web in GUI environment by lava, therefore, system is useful in diagnosing bridge at all times. Using genetic algorithm, this system can measure various bridge sensors with best gain and offset, therefore, range of measurement can be enlarged. Proposed system is certified by system-based test. .

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.1
• /
• pp.10-15
• /
• 2012

This paper considers an economic design problem of a tree-based network which is a kind of computer network. This problem can be modeling to be an objective function to minimize installation costs, on the constraints of spanning tree and maximum traffic capacity of sub tree. This problem is known to be NP-hard. To efficiently solve the problem, a tabu list coupled genetic algorithm approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic algorithm approach.

• Korean Journal of Microbiology
• /
• v.17 no.3
• /
• pp.137-151
• /
• 1979

Germinating conidia of Aspergillus nidulans diploid heterozygous for color and other genetic markers were used to direct and distinguish genetic events such as mutation, mitotic crossingover and nondisjunction in a single test after treatment with N-methyl-N'-nitro-N-nitrosoguanidine (NG), mitomycin C(MC), and chloral hydrate(CH). The following results were obtained : 1. NG reduced the survival of conidia and increased the frequencies of miototic segregants about sevenfoli over the control ; among the mitotic segregants the predominant genetic event was mitotic crossingover. NG also produced many abnormal colonies, which appeared to be of the types caused by induced semidominant lethals or chromosomal aberrations, and the aneuploid types found spontaneously. 2. After treatment with MC the survival of conidia was reduced but few abnormal colonies were produced. The frequencies of miotic segregants were increased about threefold over the control ; in the mitotic segeregants the induced genetic event was mitotic crossingover. 3. CH gave no apparent effect on the survival of conidia and the frequencies of mitotic segregants. However, CH generated abnormal colonies, very greatly, which turned out to be of the aneuploid types. This result suggests that CH interferes with the normal distribution of chromosomes in mitosis.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1645-1650
• /
• 2005

FOPDT(First-Order Plus Dead-Time) and SOPDT(Second-Order Plus Dead-Time) process, which are used as the most useful process in industry, are difficult about process identification because of the long dead-time problem and the model mismatch problem. Thus, the accuracy of process identification is the most important problem in FOPDT and SOPDT process control. In this paper, we proposed the real-coded genetic algorithm for identification of FOPDT and SOPDT processes. The proposed method using real-coding genetic algorithm shows better performance characteristic comparing with the existing an area-based identification method and a directed identification method that use step-test responses. The proposed strategy obtained useful result through a number of simulation examples.

• Computers and Concrete
• /
• v.5 no.5
• /
• pp.475-490
• /
• 2008

The paper explores the potential of applicability of Genetic programming approach (GP), adopted in this investigation, to model the combined effects of five independent variables to predict the mini-slump, the plate cohesion meter, the induced bleeding test, the J-fiber penetration value, and the compressive strength at 7 and 28 days of self-compacting slurry infiltrated fiber concrete (SIFCON). The variables investigated were the proportions of limestone powder (LSP) and sand, the dosage rates of superplasticiser (SP) and viscosity modifying agent (VMA), and water-to-binder ratio (W/B). Twenty eight mixtures were made with 10-50% LSP as replacement of cement, 0.02-0.06% VMA by mass of cement, 0.6-1.2% SP and 50-150% sand (% mass of binder) and 0.42-0.48 W/B. The proposed genetic models of the self-compacting SIFCON offer useful modelling approach regarding the mix optimisation in predicting the fluidity, the cohesion, the bleeding, the penetration, and the compressive strength.