• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.1-16
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• 2016

Yield management, which originated from the U.S. service industry, uses pricing techniques and information systems to make demand management decisions. Demand uncertainty is an important factor in the area of demand management. A key strategy to reduce the effects of demand uncertainty is substitution. The most generally known type of substitution is inventory-driven substitution, in which consumers substitute an out-of-stock product by buying a similar or other type of product. Another type of substitution is the price-driven substitution, which occurs as a result of price changes. In this research, we consider two market segments that have unique perishable products. We develop yield management optimization models with stochastic demand based on the newsvendor model where inventory-driven and price-driven substitutions are allowed between products in the two market segments. The most significant contribution of this research is that it develops analytical procedures to determine optimal solutions and considers both types of substitution. We also provide detailed theoretical analysis and numerical examples.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.

• Horticultural Science & Technology
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• v.30 no.6
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• pp.650-656
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• 2012

The aims of the experiment, conducted over three years in the Central Europe field conditions, were (1) to investigate the effect of growing period (plantings in the middle and at the end of August: $1^{st}$ and $2^{nd}$ term, respectively) on yield and chemical composition of the non-heading Chinese cabbage (Brassica rapa var. chinensis) cultivars 'Taisai', 'Pak Choy White', and 'Green Fortune', and (2) to develop regression models to evaluate the changes in crop yields as a function of weather conditions. A highest marketable yield was obtained from 'Taisai' (65.71 and 77.20 $t{\cdot}ha^{-1}$), especially in the $2^{nd}$ term of production. Low yield, observed for 'Pak Choy White' was due to its premature bolting. Almost 39% ($1^{st}$ term) and 70% ($2^{nd}$ term) of plants of this cultivar formed inflorescence shoots before harvest. The highest dry matter level was observed in the leaf petioles of 'Taisai', while 'Green Fortune' was the most abundant of carotenoids and L-ascorbic acid. The content of soluble sugars was the lowest for 'Pak Choy White'. In a phase of harvest maturity, more of the analyzed constituents were gathered by plants from earlier plantings, and differences were as follows: 4.7% (dry matter), 26.3% (carotenoids) and 22.1% (L-ascorbic acid), in comparison to $2^{nd}$ term of production. Significant increase of soluble sugars level was observed for plants from later harvest. The regression model for marketable yield of Chinese cabbage cultivar 'Taisai' as a function of maximum air temperature can predict the yield with accuracy 68%. The models for yield or bolting of 'Pak Choy White', based on extreme air temperatures and sunshine duration, were more precise (98%). It should be pointed out that Taisai could be recommended for later growing period in Central Europe conditions with regard to maximum yield potential. 'Green Fortune' was notable for its uniform yielding. To obtained plants of higher nutritional value, earlier time of cultivation should be suggested. Described models can be successfully applied for an approximate simulation of Chinese cabbage yielding.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.1
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• pp.126-134
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• 2014

This study investigates the structural strength analysis due to rib thickness of lower arm. At structural analysis, model 1 has the most deformation by comparing three models. As most equivalent stress is shown at the part connected with wheel knuckle, the strength becomes weaker in cases of three models. At fatigue analysis, model 1 becomes most unstabilized among three models. Model 3 has most fatigue life and the next model is model 2. The range of maximum harmonic response frequencies becomes 140 to 175Hz in cases of three models. Because the critical frequency at model 3 becomes highest among three models but the stress exceeds yield stress, model 3 becomes most unstabilized at vibration durability. As models 1 and 2 has less than yield stress, these models become stabilized. Model 2 becomes most favorable by comparing three models at structural, fatigue and vibration analyses. This study result can be effectively utilized with the design of lower arm by investigating prevention against damage and its strength durability.

• Journal of Fisheries and Marine Sciences Education
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• v.18 no.1
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• pp.19-30
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• 2006

For fishery stock assessment and optimum sustainable yield of anchovy in Korea, surplus production(SP) models and a maximum entropy(ME) model are employed in this paper. For determining appropriate models, five traditional SP models-Schaefer model, Schnute model, Walters and Hilborn model, Fox model, and Clarke, Yoshimoto and Pooley (CYP) model- are tested for effort and catch data of anchovy that occupies 7% in the total fisheries landings of Korea. Only CYP model of five SP models fits statistically significant at the 10% level. Estimated intrinsic growth rates are similar in both CYP and ME models, while environmental carrying capacity of the ME model is quite greater than that of the CYP model. In addition, the estimated maximum sustainable yield(MSY), 213,287 tons in the ME model is slightly higher than that of CYP model (198,364 tons). Biomass for MSY in the ME model, however, is calculated 651,000 tons which is considerably greater than that of the CYP model (322,881 tons). It is meaningful in that two models are compared for noting some implications about any significant difference of stock assessment and their potential strength and weakness.

• The Journal of Fisheries Business Administration
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• v.33 no.2
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• pp.75-98
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• 2002

As a contribution to developing fishery stock assessment, optimum sustainable yield and its international standards such as MSY, MEY, and dynamic MEY for six recommended fisheries are developed using bio-economic models. For selecting the appropriate model, five models - Schaefer, Schnute, Walters and Hilborn, Fox, and CY&P models are tested in effort and catch data of six species. Surprisingly all the models except the CY&P model failed to satisfy statistical standards such as goodness-of-fitness and reliability. Generally, the CY&P model holds good fitness and statistically significant level for all of six fisheries. However, the CY&P model for squid, where the intrinsic growth rate is high, could not explain MSY, MEY, and dynamic MEY appropriately. This study makes a contribution to develop the modified model for the intrinsic growth rate of 1. The reformulated model represents the results reasonably even though the estimated equation has not good fitness. Although most of the CY&P models appear to have good fits and validated results for some cases, these models also seem to be quite sensitive to parameters which means a more stable model should be developed and data should carefully be handled. In particular biological and technical interactions such as multispecies, predator prey relationship, age structure and mortality should be taken into account. In addition, economic factors and fishing efforts such as price, cost, technical change and a reasonable function of fishing input should simultaneously be considered.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.387-394
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• 2019

This paper presents an analytical study on the strength and stiffness of various types of truss structures. The applied models are triangular-like opened truss-wall triangular model (OTT), closed truss-wall triangular model (CTT), opened solid-wall triangular model (OST), and hypercube models defined as core-filled or core-spaced cube. The models are analyzed by numerical model analysis using DEFORM 2D/3D tool with AISI 304 stainless steel. Then, the ideal solutions for stiffness and strength are defined. Finally, the relative elastic modulus of the core-spaced model is obtained as 0.0009, which is correlated with the cancellous bone for the relative density range of 0.029-0.03, and the relative elastic modulus for the core-filled model is obtained as 0.0015, which is correlated with cancellous bone for the relative density range of 0.035-0.036. For the relative compressive yield strength, the OTT reasonably agrees with the cancellous bone for the relative density of 0.042 and the relative compressive strength of 0.05. The CTT and OST are in good agreement at the relative density of 0.013 and the relative compressive yield strength of 0.002. The hypercube models can be used for the cancellous bone for stiffness, and the triangular models can be used for the cancellous bone for strength. However, none of the models can be used to replace the compact bone because it requires much higher stiffness and strength. In the near future, compact bone replacement must be further studied. In addition, previously mentioned models should be developed further.

• Journal of Climate Change Research
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• v.6 no.1
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• pp.21-31
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• 2015

Various crop models have been extensively used for estimation of the crop yields. Compared to the other models, the EPIC model uses a unified approach to simulate more than 100 types of crops. It has been successfully applied in simulating crop yields for various combinations of weather conditions, soil properties, crops, and management schemes in many countries. The objective of this study was to estimate the rice and maize yield in South Korea using the EPIC model. The input datasets for the 30 types in the 11 categories were created for the EPIC model. The EPIC model simulated rice and maize yields. The performance of the EPIC model was evaluated with the goodness-of-fit measures including Root Mean Square Error (RMSE), Relative Error (RE), Nash-Sutcliffe Efficiency Coefficient (NSEC), Mean Absolute Error (MAE), and Pearson Correelation Coefficient (r). The rice yield showed to more high accuracy than maize yield on four type of method without NSEC. Theses results showed that the EPIC model better simulated rice yields than maize yields. The results suggest that the EPIC crop model can be useful to estimate crop yield in South Korea.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.7
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• pp.915-921
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• 2006

Various random regression models with different order of Legendre polynomials for permanent environmental and genetic effects were constructed to predict future milk yield of Holstein cows in Korea. A total of 257,908 test-day (TD) milk yield records from a total of 28,135 cows belonging to 1,090 herds were considered for estimating (co)variance of the random covariate coefficients using an expectation-maximization REML algorithm in an animal mixed model. The variances did not change much between the models, having different order of Legendre polynomial, but a decreasing trend was observed with increase in the order of Legendre polynomial in the model. The R-squared value of the model increased and the residual variance reduced with the increase in order of Legendre polynomial in the model. Therefore, a model with $5^{th}$ order of Legendre polynomial was considered for predicting future milk yield. For predicting the future milk yield of cows, 132,771 TD records from 28,135 cows were randomly selected from the above data by way of preceding partial TD record, and then future milk yields were estimated using incomplete records from each cow randomly retained. Results suggested that we could predict the next four months milk yield with an error deviation of 4 kg. The correlation of more than 70% between predicted and observed values was estimated for the next four months milk yield. Even using only 3 TD records of some cows, the average milk yield of Korean Holstein cows would be predicted with high accuracy if compared with observed milk yield. Persistency of each cow was estimated which might be useful for selecting the cows with higher persistency. The results of the present study suggested the use of a $5^{th}$ order Legendre polynomial to predict the future milk yield of each cow.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.127-132
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• 2011

In this study, calculation results of sediments yield prediction models were compared with the amount of dredging data for the Inje, Gangwon mountain region of Korea. MSDPM and LADMP were used as a sediments prediction model which was calibrated and modified to calculate the sediments yield of Korean mountain region. Both sediments yield prediction models were modified by using Threshold Maximum Rainfall Intensity and Total Minimum Rainfall Intensity and correction coefficient. After comparing with the amount of dredging, it was found that results of MSDPM is more accurate than the results of LADMP. Difference of results of MSDPM and the amount of dredging is 27.6% and difference of results of LADMP and the amount of dredging is 50.6%. Both sediments yield prediction models which were calibrated in this study can be used to calculate the sediments yield for the Korean mountain region.