• Journal of Navigation and Port Research
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• v.29 no.2
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• pp.141-146
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• 2005

For a long time, genetic algorithms have been recognized as a new method to solve difficult and complex problems and the performance of genetic algorithms depends on genetic operators, especially crossover operator. Various problems like the traveling salesman problem, the transportation problem or the job shop problem, in logistics engineering can be modeled as a sequencing problem This paper proposes modified genetic crossover operators to be used at various sequencing problems and uses the traveling salesman problem to be applied to a real world problem like the delivery problem and the vehicle routing problem as a benchmark problem Because the proposed operators use parental information as well as network information, they could show better efficiency in performance and computation time than conventional operators.

• Advances in environmental research
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• v.1 no.1
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• pp.57-68
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• 2012

Recent studies showed that air pollution is a risk factor for hospitalization for chronic obstructive pulmonary disease (COPD). However, there is limited evidence to suggest which subpopulations are at higher risk from air pollution. This study was undertaken to examine the modifying effect of specific secondary diagnosis (including hypertension, diabetes, pneumonia, congestive heart failure) on the relationship between hospital admissions for COPD and ambient air pollutants concentrations. Hospital admissions for COPD and ambient air pollution data for Taipei were obtained for the period from 1999-2009. The relative risk of hospital admissions for COPD was estimated using a case-crossover approach. None of the secondary diagnosis we examined showed much evidence of effect modification.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.275-284
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• 1999

The TTP(TimeTabling Problem) for a university which should be made every term is very difficult problem to schedule because each component must satisfy all fixed constraints. This TTP, therefore, is solved by several heuristic methods. In this paper, applying PPEP(Parallel Population Evolution Programs) for the TTP, we try to find the approximated optimal solution by maintaining independence of each subpopulation and by searching the wide feasible solution. In addition, we present the problem to be appeared when used PMX(Partially mapped crossover)operator for the long chromosomes and then propose GBX (Gene_Based crossover)operator which can complement it. Finally, experimental results are presented comparing EP(Evolution Programs) and PPEP, then GBX which has the random genes and the selected genes on a real TTP.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.285-295
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• 2006

As more generic drugs become available, the quality, safety, and efficacy of generic drugs have become a public concern. Specifically, drug interchangeability among generic copies of the same brand-name drug is a safety concern. This research proposes a Bayesian method for assessing bioequivalence between two generic copies of the same brand-name drug from two independent $2{\times}2$ crossover design experiments. Uninformative priors are considered for general use and the posterior distribution of the difference of two generic drug effects is derived from which the highest probability density interval can be evaluated. Examples are presented for illustration.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.383-386
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• 2002

In this paper, we investigated the pattern recognition performance of the numeric patterns (from 0 to 9) using DNA coding method. The pattern recognition performance of the DNA coding method is compared to the that of the GA(Genetic Algorithm). GA searches effectively an optimal solution via the artificial evolution of individual group of binary string using binary coding, while DNA coding method uses four-type bases denoted by A(Adenine), C(Cytosine), G(Guanine) and T(Thymine), The pattern recognition performance of GA and DNA coding method is evaluated by using the same genetic operators(crossover and mutation) and the crossover probability and mutation probability are set the same value to the both methods. The DNA coding method has better characteristics over genetic algorithms (GA). The reasons for this outstanding performance is multiple possible solution presentation in one string and variable solution string length.

• Industrial Engineering and Management Systems
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• v.10 no.4
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• pp.247-254
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• 2011

In this paper, we study a single-machine scheduling problem with deteriorating processing time of jobs and multiple rate-modifying activities which reset deteriorated processing time to the original processing time. In this situation, the objective function is to minimize total completion time. First, we formulate an integer programming model. Since the model is difficult to solve as the size of real problem being very large, we design an improved genetic algorithm called adaptive genetic algorithm (AGA) with spontaneously adjusting crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with the conventional GAs with various combinations of crossover and mutation rates.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.189-203
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• 2002

In this paper we compare the performances of adaptive operators in genetic algorithm. For the adaptive operators, the crossover and mutation operators of genetic algorithm are considered. One fuzzy logic controller is developed in this paper and two heuristics is presented from conventional works for constructing the operators. The fuzzy logic controller and two conventional heuristics adaptively regulate the rates of the operators during genetic search process. All the algorithms are tested and analyzed in numerical examples. Finally, the best algorithm is recommended.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.749-754
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• 2014

In this paper, we suggest tree-structure-aware GP (Genetic Programming) operators that heed tree distributions in structure space and their possible structural difficulties. The main idea of the proposed GP operators is to place the generated offspring of crossover and/or mutation in a specified region of tree structure space insofar as possible by biasing the tree structures of the altered subtrees, taking into account the observation that most solutions are found in that region. To demonstrate the effectiveness of the proposed approach, experiments on the binomial-3 regression, multiplexor and even parity problems are performed. The results show that the results using the proposed tree-structure-aware operators are superior to the results of standard GP for all three test problems in both success rate and number of evaluations.

• 대한예방의학회:학술대회논문집
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• 2000.10a
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• pp.112-113
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• 2000

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.317-322
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• 2004

In this paper, It was describe the processes of development of HiFi speaker system. Woofer and tweeter were fabricated by unskilled students and their 1.5 parameters were identified by known mass method. Based on T-S parameters port enclosure was designed and built by means of software. Acoustic radiation phenomena of port enclosure were simulated and compared to test result. Acoustic pressure difference between lower frequency and higher frequency was flattened by adopting optimal crossover network. Finally, built HiFi speaker system was showed good sound quality and sound pressure and electrical impedance was well agreed with test results each other.