• The Korean Journal of Pesticide Science
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• v.20 no.3
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• pp.264-270
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• 2016

This study was conducted to compare of the pesticide residue amounts in fruit trees applied by different sprayers and spray volumes. Apple tree was used as a sample tree, and speed sprayer, power sprayer and knapsack motorized sprayer were tested. For similar sprayer and spray volume, the concentration of fluquinconazole and flusilazole in apple leaves were obtained respectively, for speed sprayer 8.33 and 2.15 mg/kg, for power sprayer 4.56 and 1.10 mg/kg, and for knapsack 4.55 and 1.12 mg/kg. The results showed that the treatment using speed sprayer had highest efficiency. The pesticide residues in apple leaves sprayed by 3 different spray volumes (560, 336 and 230 L/10a) using speed sprayer were 10.76 mg/kg, 8.32 mg/kg, 6.04 mg/kg on fluqinconazle and 3.04 mg/kg, 2.14 mg/kg and 1.47 mg/kg on flusilazole, respectively, indicating that the higher the volume, the higher the residues. The results from this study can be used as scientific basis for evaluating the field trial data for pesticide registration and the spray volume setting for fruit trees in Korea.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.57-63
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• 2012

Software release planning model of software product lines was formulated as a precedence-constrained multiple 0-1 knapsack problem. The purpose of the model was to maximize the total profit of an entire set of selected features in a software product line over a multi-release planning horizon. The solution approach is a dynamic programming procedure. Feasible solutions at each stage in dynamic programming are determined by using backward dynamic programming approach while dynamic programming for multi-release planning is forward approach. The pre-processing procedure with a heuristic and reduction algorithm was applied to the single-release problems corresponding to each stage in multi-release dynamic programming in order to reduce the problem size. The heuristic algorithm is used to find a lower bound to the problem. The reduction method makes use of the lower bound to fix a number of variables at either 0 or 1. Then the reduced problem can be solved easily by the dynamic programming approaches. These procedures keep on going until release t = T. A numerical example was developed to show how well the solution procedures in this research works on it. Future work in this area could include the development of a heuristic to obtain lower bounds closer to the optimal solution to the model in this article, as well as computational test of the heuristic algorithm and the exact solution approach developed in this paper. Also, more constraints reflecting the characteristics of software product lines may be added to the model. For instance, other resources such as multiple teams, each developing one product or a platform in a software product line could be added to the model.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.92-99
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• 2004

We consider the ATM switching node location problem (ANLP). In this problem, there are two kinds of facilities, hub facilities and remote facilities, with different capacities and installation costs. We are given a set of customers with each demand requirements, a set of candidate installation sites of facilities, and connection costs between facilities. We need to determine the locations to place facilities, the number of facilities for each selected location, the set of customers who are connected to each installed hub via installed remote facilities with minimum cost, while satisfying demand requirements of each customer. We formulate this problem as a general integer programming problem and solve it to optimality. In this paper, we present a preprocessing procedure to tighten the formulation and develop a branch-and-price algorithm. In the algorithm, we consider the integer knapsack problem as the column generation problem. Computational experiments show that the algorithm gives optimal solutions in a reasonable time.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.3
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• pp.93-107
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• 1999

We consider the development of an integer programming model and algorithm for the ATM switching node location problem. There are two kinds of facilities, hub facilities and remote facilities, with different capacities and installation costs. Each customer needs to be connected to one or more hub facilities via remote facilities, where the hub(remote) facilities need to be installed at the same candidate installation site of hub(remote) facility. We are given a set of customers with each demand requirements, a set of candidate installation sites of facilities, and connection costs between facilities, We need to determine the locations to place facilities, the number of facilities for each selected location, the set of customers who are connected to each installed hub facilities via installed remote facilities with minimum costs, while satisfying demand requirements of each customer. We formulate this problem as a general integer programming problem and solve it to optimality. In this paper, we develop a branch-and-cut algorithm with path variables. In the algorithm, we consider the integer knapsack polytope and derive valid inequalities. Computational experiments show that the algorithm works well in the real world situation. The results of this research can be used to develop optimization algorithms to solve capacitated facility location problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.514-517
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• 1996

In solving multi-level knapsack problems, conventional heuristic approaches often assume a short-sighted plan within a static decision enviornment to find a near optimal solution. These conventional approaches are inflexible, and lack the ability to adapt to different problem structures. This research approaches the problem from a totally different viewpoint, and a new method is designed and implemented. This method performs intelligent actions based on memories of historic data and learning. These actions are developed not only by observing the attributes of the optimal solution, the solution space, and its corresponding path to the optimal solution, but also by applying human intelligence, experience, and intuition with respect to the search strategies. The method intensifies, or diversifies the search process appropriately in time and space. In order to create a good neighborhood structure, this method uses two powerful choice rules that emphasize the impact of candidate variables on the current solution with respect to their profit contribution. A side effect of so-called "pseudo moves", similar to "aspirations", supports these choice rules during the evaluation process. For the purpose of visiting as many relevant points as possible, strategic oscillation between feasible and infeasible solutions around the boundary is applied for intensification. To avoid redundant moves, short-term (tabu-lists), intermediate-term (cycle detection), and long-term (recording frequency and significant solutions for diversification) memories are used. Test results show that among the 45 generated problems (these problems pose significant or insurmountable challenges to exact methods) the approach produces the optimal solutions in 39 cases.lutions in 39 cases.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.365-378
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• 2013

In Wireless Mesh Networks (WMNs), we usually deploy multiple Internet Gateways (IGWs) to improve the capacity of WMNs. As most of the traffic is oriented towards the Internet and may not be distributed evenly among different IGWs, some IGWs may suffer from bottleneck problem. To solve the IGW bottleneck problem, we propose an efficient scheme to balance the load among different IGWs within a WMN. Our proposed load-balancing scheme consists of two parts: a traffic load calculation module and a traffic load migration algorithm. The IGW can judge whether the congestion has occurred or will occur by using a linear smoothing forecasting method. When the IGW detects that the congestion has occurred or will occur, it will firstly select another available IGW that has the lightest traffic load as the secondary IGW and then inform some mesh routers (MPs) which have been selected by using the Knapsack Algorithm to change to the secondary IGW. The MPs can return to their primary IGW by using a regression algorithm. Our Qualnet 5.0 experiment results show that our proposed scheme gives up to 18% end-to-end delay improvement compared with the existing schemes.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.3
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• pp.69-81
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• 2006

In this paper, an adaptive algorithm is proposed in streaming MPEG-4 contents with fluctuating resource amount such as throughput of network conditions. In the area of adaptive streaming issue, a lot of researches have been made on how to represent encoded media(such as video) bitstream in scalable way. By contrast, MPEG-4 supports object-based multimedia content which is composed of various types of media streams such as audio, video, image and other graphical elements. Thus, it can be more effective to provide individual media streams in scalable way for streaming object-based content to heterogeneous environment. The proposed method provides the multiple media streams corresponding to an object with different qualities and bit rate in order to support object based scalability to the MPEG-4 content. In addition, an optimal selection of the multiple streams for each object to meet a given constraint is proposed. The selection process is adopted a multiple choice knapsack problem with multi-step selection for the MPEG-4 objects with different scalability levels. The proposed algorithm enforces the optimal selection process to maintain the perceptual qualities of more important objects at the best effort. The experimental results show that the set of selected media stream for presenting objects meets a current transmission condition with more high perceptual quality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.770-771
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• 2015

In this paper, we proposed and implemented the automation of cable drum scheduling which is required a considerable construction cost for electrical equipment in power plant. Implemented cable drum scheduling can be reduced the calculation time of cable drum scheduling, and it is possible to minimize the consuming time of cable drum scheduling than conventional methods. Some experiments are conducted to verify the proposed method, and as a result, the automation of cable drum scheduling is well performed, enabling cables can be optimized and scheduled to fit the drum capacity with productivity enhancement of electrical installations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.11 no.18
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• pp.7-15
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• 1988

This study is concerned with selecting mutually dependent quality improvement alternatives with resource constraints. These qualify improvement alternatives art different fro the tradition at alternatives which are independent from each other. In other words, selection of any improvement alternative requires other related specific improvement. Also the overall product quality in a multi stage manufacturing process is characterized by a complex multiplication method rather than a simple addition method which dose not allow to solve a linear knapsack problem despite its popularity in the traditional study. This study suggests a non-linear integer programming model for selecting mutually dependent quality improvement alternatives in multi-stage manufacturing process. In order to apply the model to selecting alternatives. This study also suggests a heuristic mode1 based on a dynamic programming model which is more practical than the non-linear integer programming model. The logic of the heuristic model enables 1) to estimate improvement effectiveness values on all improvement alternatives specifically defined for this study. 2) to arrange the effectiveness values in a descending order, and 3) to select the best one among the alternatives based on their forward and backward linkage relationships. This process repeats to selects other best alternatives within the resource constraints. This process is presented in a Computer programming in Appendix A. Alsc a numerical example of model application is presented in Chapter 4.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.99-117
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• 2018

This study has investigated Linear Programming (LP) applications to special decision making problems in managerial accounting with the help of spreadsheet Solver tools. It uses scenario approaches to case examples having three products and three resources in make-and-supply business operations, which is applicable to cases having more variables and constraints. Integer Programmings (IP) are applied in order to model situations when products are better valued in integer values or logical constraints are required. Three cases in one-time-only special order decisions include Goal Programming approach, Knapsack problems with 0/1 selections, and fixed-charge 0/1 integer modelling techniques for set-up operation costs. For the decisions in outsourcing problems, opportunity-costs of resources expressed by shadow-prices are considered to determine their precise contributions. It has also shown that the improvement in work-shop operation for an unprofitable product must overcome its 'reduced cost' by the sum of direct manufacturing cost savings and its shadow-price contributions. This paper has demonstrated how various real situations of special decision problem in managerial accounting can be approached without mistakes by using LP's and IP's, and how students both in accounting and management science can acquire LP skills in their education.