• The Journal of Information Systems
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• v.16 no.1
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• pp.111-133
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• 2007

The purpose of this study is to present a new function point estimation approach for the Object-Oriented information systems. In order to fulfill this purpose, we first review the literature on Function Point Analysis of IFPUG, Unified Modeling Language, and Unified Process. Then, we derive a method and rules for estimating Function Points based on Use Cases and Class Diagrams. To analyze the appropriateness of the proposed approach, we conduct the empirical testing. 143 use cases are collected from production, marketing, distribution, sales, and other areas from the Object-Oriented systems development projects. We compare our new approach with the existing methods that are usually used for traditional systems development projects. The results show that our proposed approach is more appropriate for the Object-Oriented environment.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.103-117
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• 2011

Recently, the service innovation is getting interests among innovation researchers. After reviewing the Lancasterian approach concerning the service innovation, this paper explains concretely the innovation in the cultural industry, specifically online game industry, using Lancasterian approach. Combining Lancasterian approach and the value chains in the cultural industry systematically, we draw both implications in theory and policy. Theoretically, the innovation in the cultural industry needs interdisciplinary research due to the inclusion of diverse innovation natures-technical, content, and marketing innovation. Also this paper suggests policy makers to apply research and development(R&D) concept in the manufacturing sector to the cultural industry in which content R&D means the creation of new concepts or new development of the service.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.139-149
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• 1994

In many project-oriented production systems, e. g., shipyards or large-scale steel products manufacturing, resource loading by an activity is flexible, and the activity duration is a function of resource allocation. For example, if one doubles the size of the crew assigned to perform an activity, it may be feasible to complete the activity in half the duration. Such flexibility has been modeled by Weglarz [13] and by Leachman, Dincerler, and Kim [7[ in extended formulations of the resource-constrained poject scheduling problem. This paper presents a new algorithmic approach to the problem that combines the ideas proposed by the aforementioned authors. The method we propose involves a two-step approach : (1) solve the resource-constrained scheduling problem using a heuristic, and (2) using this schedule as an initial feasible solution, find improved resource allocations by solving a linear programming model. We provide computational results indicating the superiority of this approach to previous methodology for the resource-constrained scheduling problem. Extensions to the model to admit overlap relationship of the activities also are presented.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.35-51
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• 2016

This paper proposes a new approximate approach to calculate the order fill rate and the probability of filling an entire customer order immediately from the shelf in a business environment under purchase dependence characterized by customer purchase patterns observed in such areas as marketing, manufacturing systems, and distribution systems. The new approximate approach divides customer orders into item orders and calculates fill rates of all order types to approximate the order fill rate. We develop a greed iterative search algorithm (GISA) based on the Gauss-Seidel method to avoid dimensionality and prevent the solution divergence for larger instances. Through the computational analysis that compares the GISA with the simulation, we demonstrate that the GISA is a dependable algorithm for deriving the stationary joint distribution of on-hand inventories in the type-K pure system. We also present some managerial insights.

• MALSORI
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• no.44
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• pp.115-130
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• 2002

Voice input is often required in many new application environments, but the low rate of speech recognition makes it difficult to extend its application. Previous approaches were to raise the accuracy of the recognition by post-processing of the recognition results, which were all lexical-oriented. We suggest a new semantic-oriented approach in speech recognition error correction. Through experiments using a speech-driven in-vehicle telematics information application, we show the excellent performance of our approach and some advantages it has as a semantic-oriented approach over a pure lexical-oriented approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.146-154
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• 2004

Evaluating the risk of collision quantitatively plays a key role in developing the expert system of navigation and collision avoidance. This study suggested and developed a new approach to the evaluation by using the sech function as an alternative to the existing methods of appraising the collision risk. This study also investigated and built up theoretically how to determine the gradient coefficients in this approach and suggested the appropriate values as much as applicable. Finally this study analyzed thoroughly how to determine the threshold function of avoiding time and developed the appropriate equation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.410-420
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• 1994

In many project-oriented production systems, e.g., shipyards or large-scale steel products manufacturing, resource loading by an activity is flexible, and the activity duration is a function of resource allocation. For example, if one doubles the size of the crew assigned to perform an activity, it may be feasible to complete the activity in half the duration. Such flexibility has been modeled by Weglarz [131 and by Leachman, Dincerler, and Kim [7] in extended formulations of the resource-constrained project scheduling problem. This paper presents a new algorithmic approach to the problem that combines the ideas proposed by the aforementioned authors. The method we propose involves a two-step approach: (1) solve the resource-constrained scheduling problem using a heuristic, and (2) using this schedule as an initial feasible solution, find improved resource allocations by solving a linear programming model. We provide computational results indicating the superiority of this approach to previous methodology for the resource-constrained scheduling problem. Extensions to the model to admit overlap relationships of the activities also are presented.

• Food Science of Animal Resources
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• v.43 no.2
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• pp.374-381
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• 2023

In a previous study, 'response surface methodology (RSM) using a fullest balanced model' was proposed to improve the optimization of food processing when a standard second-order model has a significant lack of fit. However, that methodology can be used when each factor of the experimental design has five levels. In response surface experiments for optimization, not only five-level designs, but also three-level designs are used. Therefore, the present study aimed to improve the optimization of food processing when the experimental factors have three levels through a new approach to RSM. This approach employs three-step modeling based on a second-order model, a balanced higher-order model, and a balanced highest-order model. The dataset from the experimental data in a three-level, two-factor central composite design in a previous research was used to illustrate three-step modeling and the subsequent optimization. The proposed approach to RSM predicted improved results of optimization, which are different from the predicted optimization results in the previous research.

• 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.