• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.155-164
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• 2012

As the global market becomes more competitive, manufacturing industries face relentless pressure caused by a growing tendency of greater varieties of products, shorter manufacturing cycles and more sophisticated customer requirements. Efficient and effective supplier selection and order allocation decisions are, therefore, important decisions for a manufacturer to ensure stable material flows in a highly competitive supply chain, in particular, when customers are willing to accept products with less desirable product attributes (e.g., color, delivery date) for economic reasons. This paper attempts to solve optimally the challenging problem of supplier selection and order allocation, taking into consideration the customer flexibility for a manufacturer producing multi-products to satisfy the customers' demands in a multi period planning horizon. A new mixed integer programming model is developed to describe the behavior of the supply chain. The objective is to maximize the manufacturer's total profit subject to various operating constraints of the supply chain. Due to the complexity and non-deterministic polynomial-time (NP)-hard nature of the problem, an improved genetic approach is proposed to solve the problem optimally. This approach differs from a canonical genetic algorithm in three aspects: a new selection method to reduce the chance of premature convergence and two problem-specific repair heuristics to guarantee feasibility of the solutions. The results of applying the proposed approach to solve a set of randomly generated test problems clearly demonstrate its excellent performance. When compared with applying the canonical genetic algorithm to locate optimal solutions, the average improvement in the solution quality amounts to as high as ten percent.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.75-87
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• 2009

We propose in this paper a novel approach to image fusion in which the fusion rule is guided by optimizing an image clarity function. A Genetic Algorithm is used to stochastically select, comparative to the clarity function, the optimum block from among the source images. A novel nested Genetic Algorithm with gifted individuals found through bombardment of genes by the mutation operator is designed and implemented. Convergence of the algorithm is analytically and empirically examined and statistically compared (MANOVA) with the canonical GA using 3 test functions commonly used in the GA literature. The resulting GA is invariant to parameters and population size, and a minimal size of 20 individuals is found to be sufficient in the tests. In the fusion application, each individual in the population is a finite sequence of discrete values that represent input blocks. Performance of the proposed technique applied to image fusion experiments, is characterized in terms of Mutual Information (MI) as the output quality measure. The method is tested with C=2 input images. The results of the proposed scheme indicate a practical and attractive alternative to current multi-focus image fusion techniques.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.8
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• pp.1074-1080
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• 2017

Objective: The growth, carcass and retail cut yield records on 1,428 Hanwoo steers obtained through progeny testing were analyzed in this study, and their heritability and genetic relationships among the traits were estimated using animal models. Methods: Two different models were compared in this study. Each model was fitted for different fixed class effects, date of slaughter for carcass traits and batch of progeny test live measurement traits, and a choice of covariates (carcass weight in Model 1 or backfat thickness in Model 2) for carcass traits. Results: The differences in body composition among individuals were deemed being unaffected by their age at slaughter, except for carcass weight and backfat thickness. Heritability estimates of body size measurements were 0.21 to 0.36. Heritability estimates of retail cut percentage were high (0.56 from Model 1 and 0.47 from Model 2). And the heritability estimates for loin muscle percentage were 0.36 from Model 1 and 0.42 from Model 2, which were high enough to consider direct selection on carcass cutability traits as effective. The genetic correlations between body size measurements and retail cut ratio (RCR) were close to zero. But, some negative genetic correlations were found with chest girths measured at yearling (Model 1) or at 24 months of age or with chest widths. Loin muscle ratio (LMR) was genetically negatively correlated with body weights or body size measurements, in general in Model 1. These relationships were low close to zero but positive in Model 2. Phenotypic correlation between cutability traits (RCR, LMR) and live body size measurements were moderate and negative in Model 1 while those in Model 2 were all close to zero. Conclusion: Therefore, the body weights or linear body measurements at an earlier age may not be the most desirable selection traits for exploitation of correlated responses to improve loin muscle or lean meat yield.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.217-222
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• 2011

Genetic algorithms are one of the most important methods used to solve the Traveling Salesman Problem. Therefore, many researchers have tried to improve the Genetic Algorithm by using different methods and operations in order to find the optimal solution within reasonable time. This paper intends to find a new approach that adopts an improved genetic algorithm to solve the Traveling Salesman Problem, and compare with the well known heuristic method, namely, Kohonen Self-Organizing Map by using different data sets of symmetric TSP from TSPLIB. In order to improve the search process for the optimal solution, the proposed approach consists of three strategies: two separate tour segments sets, the improved crossover operator, and the improved mutation operator. The two separate tour segments sets are construction heuristic which produces tour of the first generation with low cost. The improved crossover operator finds the candidate fine tour segments in parents and preserves them for descendants. The mutation operator is an operator which can optimize a chromosome with mutation successfully by altering the mutation probability dynamically. The two improved operators can be used to avoid the premature convergence. Simulation experiments are executed to investigate the quality of the solution and convergence speed by using a representative set of test problems taken from TSPLIB. The results of a comparison between the new approach using the improved genetic algorithm and the Kohonen Self-Organizing Map show that the new approach yields better results for problems up to 200 cities.

• Journal of Animal Science and Technology
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• v.58 no.10
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• pp.38.1-38.6
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• 2016

Background: Despite the importance of relationships between somatic cell score (SCS) and currently selected traits (milk, fat and protein yield) of Holstein cows, there was a lack of comprehensive literature for it in Iran. Therefore we tried to examine heritabilities and relationships between these traits using a fixed-regression animal model and Bayesian inference. The data set consisted of 1,078,966 test-day observations from 146,765 primiparous daughters of 1930 sires, with calvings from 2002 to 2013. Results: Marginal posterior means of heritability estimates for SCS ($0.03{\pm}0.002$) were distinctly lower than those for milk ($0.204{\pm}0.006$), fat ($0.096{\pm}0.004$) and protein ($0.147{\pm}0.005$) yields. In the case of phenotypic correlations, the relationships between production and SCS were near zero at the beginning of lactation but become increasingly negative as days in milk increased. Although all environmental correlations between production and SCS were negative ($-0.177{\pm}0.007$, $-0.165{\pm}0.008$ and $-0.152{\pm}0.007$ between SCS and milk, fat, and protein yield, respectively), slightly antagonistic genetic correlations were found; with posterior mean of relationships ranging from $0.01{\pm}0.039$ to $0.11{\pm}0.036$. This genetic opposition was distinctly higher for protein than for fat. Conclusion: Although small, the positive genetic correlations suggest some genetic antagonism between desired increased milk production and reduced SCS (i.e., single-trait selection for increased milk production will also increase SCS).

• Microbiology and Biotechnology Letters
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• v.14 no.2
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• pp.187-192
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• 1986

The inoculation effect of the highly nitrogen fixing strains of R. japonicum were tested in the 3 kinds of soil with different cultural history onto Gycine max cv. Jang-yeob. The nodulation and nitrogen fixation activity in 3 test soils all showed the great increase in inoculated group compared to the non-inoculated group. The plant dry weight of the in-oculated groups were increased about 10% than that of the non-inoculated groups. The numerical index of the increase in total nitrogen fixation activity were 238% in the pre-cultivated, 266% in the immatured and 157% in the matured soil and these results suggested the clear effect of inoculation. Among the strains tested, R. japonicum R214 and Rl38 showed the excellent inoculation effect.

• Journal of Animal Science and Technology
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• v.44 no.4
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• pp.377-382
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• 2002

This study was carried out for the simultaneous genetic evaluation of swine breeds from the seedstock farms in Korea. The performance tested production records of 96,842 heads and the litter records of 90,396 litters from 1995 to 2001 were analyzed to estimate the breeding values and the breed effects of days to 90kg, daily gain, back fat thickness, loin muscle area, lean meat percent, total litter size and number born alive from Landrace, Yorkshire and Duroc. Estimated breed effects of traits had shown the characteristics of the breeds. Landrace was superior in back fat thickness and lean meat percent to other breeds. Yorkshire had shown good performance in lean meat percent, loin muscle area, total litter size and number born alive. Duroc was superior to the other breeds in days to 90kg and daily gain. Conclusively, the multi-breed genetic evaluation would result in higher connectedness and provide convenience for the routine genetic evaluation process of swine performance and reproduction test.

• The KIPS Transactions:PartD
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• v.18D no.2
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• pp.89-100
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• 2011

The CNV (Copy Number Variation) which is one of the genetic structural variations in human genome is closely related with the function of gene. In particular, the genome-wide association studies for genetic diseased persons have been researched. However, there have been few studies which infer the genetic function of CNV with normal human. In this paper, we propose the analysis method to reveal the functional relationship between common CNV and genes without considering their genomic loci. To achieve that, we propose the data integration method for heterogeneity biological data and novel measurement which can calculate the correlation between common CNV and genes. To verify the significance of proposed method, we has experimented several verification tests with GO database. The result showed that the novel measurement had enough significance compared with random test and the proposed method could systematically produce the candidates of genetic function which have strong correlation with common CNV.

• Korean Journal of Environmental Biology
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• v.26 no.3
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• pp.264-269
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• 2008

This study was intended to test the feasibility of genetic analysis of wintering population of geese using their feces samples. This noninvasive approach is quite significant and effective because we do not need to capture or harm geese to obtain the samples. We collected the feces from two different populations of wintering geese in Korea in 2007. Finally thirty two feces were analyzed through a molecular genetic method. As a result, 14 haplotypes were identified and classified into two groups, white-fronted geese (Anser albifrons) and bean geese (Anser fabalis). We established the method to make molecular genetic experiment more efficient using the feces. This study has a significance as the first genetic result on wintering population of geese in Korea using noninvasive sampling method.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1573-1578
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• 2020

Objective: Milk fatty acid (FA) is a main nutritional component that markedly effects human health. Intentional modification of the FA profile has the potential to improve milk quality. This study aimed at the factors affecting elevated FA levels and the estimation of the genetic parameters for milk FAs in the Korean Holstein population. Methods: Total 885,249 repeated test-day milk records including, milk yield, saturated fatty acids (SFA), polyunsaturated fatty acids (PUFA), monounsaturated fatty acids (MUFA), total unsaturated fatty acids (TUFA), fat and protein percentages were analyzed using CombiFoss FT+ system (Foss Analytical A/S, Denmark). Genetic parameters were estimated by the restricted maximum likelihood procedure based on the repeatability model using the Wombat program. Results: The FA profile varies along with the lactation and the energy balance (EB). With the negative EB in early lactation, mobilization of body fat reserves elevates the desirable FA levels. As a result of that, milk quality is increased by means of nutritionally and usability aspects during the early lactation. Moreover, heritability estimates for SFA, MUFA, PUFA, TUFA were 0.33, 0.42, 0.37, 0.41 respectively. According to the parity wise heritability analysis, first parity cows had relatively lower heritability for SFAs (0.19) than later parities (0.28). Conclusion: Genetic parameters indicated that FAs were under stronger genetic control. Therefore, we suggest implementing animal breeding programs towards improving the milk FA profile.