• Journal of the Korean Home Economics Association
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• v.46 no.10
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• pp.133-146
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• 2008

This study investgates the factors influencing the levels of consumer satisfaction and life satisfaction of resident foreigners in Korea. The data were collected through a structured self-administered survey and 545 foreigners who lived in Korea for more than 3 months, with age over 20 participated as respondents. A research framework was formulated based on the resource constraint hypothesis and the study investigated the impact of information resource(human, media and internet information source) and consumer resource(monthly income, language ability and consumer proficiency) on the levels of consumer satisfaction and life satisfaction. The results from data analysis can be summarized as follows; First, analysis of consumer problems of resident foreigners in Korea indicated that resident foreigners recognize a burden for residence cost, food expense and education fee. Most of resident foreigners in Korea are found to use small local shops most often indicating they may experience adverse market environment due to resource constraint such as language or psychological barrier, and most of the respondents answered that the most often used payment method was cash. Furthermore, resident foreigners in Korea responded that lack of language service, lack of information provision, inability to use certain goods and services are the common cause of consumer dissatisfaction, as well as price and quality problems. Second, the level of consumer satisfaction (2.96 in 4.0) is higher than the level of life satisfaction (2.63 in 4.0). Third, the level of life satisfaction is significantly influenced by Korean language ability and the level of consumer satisfaction. The level of consumer satisfaction is by the media information source usage and consumer claim experience. Fourth, the level of consumer satisfaction is found to be the variable with the strongest causal relationship with the level of life satisfaction.

• IE interfaces
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• v.19 no.3
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• pp.190-201
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• 2006

With the rapid growth in the demand and supply of web service, the search for superior services has become a prominent issue. Furthermore, much emphasis and attention are being placed on composite web services, where individual services are combined together to form a single workflow to satisfy the demand of the customers. In today's era of excessive expansion of web services, this study intends to propose the execution plan architecture for composite web services to accomplish the following three goals. The first goal is to derive a feasible plan which maximize user satisfaction for composite web services by implementing an execution plan architecture that reflects the Quality of Service criteria. Secondly, this study also aims at analyzing and selecting the indexes that adequately reflects its quality and its nonfunctional property. Finally, this study intends to apply the concept of constraint satisfaction problem and heuristics to reduce the execution duration of the process.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.227-233
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• 2004

Complex scheduling problems are related to planning, scheduling, constraint satisfaction problems, object-oriented concepts, and agent systems. Human preference-driven scheduling technique was to solve complex scheduling problems using constraint satisfaction problems and object-oriented concepts. We have tried to apply human preference-driven scheduling technique to reservation problems. For customer's satisfaction, we have considered customer's preferences in the reservation scheduling. The technique of reservation scheduling proposed in this thesis is based on object-oriented concepts. 1'o consider the over all satisfaction, the events of every object are alloted to the board along its priority. Constraints to reservation scheduling are classified to global and local. The definition of board and information of every event are global constraints and the preferences to object's board slots are local constraints. We have applied look-ahead technology to reservation scheduling in order to minimize backtracking not to fail the allotment of events.

• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.27-34
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• 2019

The course timetabling problem is a kind of very complex combinatorial optimization problems, which is known as an NP-complete problem. Sometimes a given course timetabling problem can be accompanied by many constraints. At this time, even if only one constraint is violated, it can be an infeasible timetable. Therefore, it is very difficult to make an automated course timetabling system for a complex real-world course timetabling problem. This paper introduces an automated course timetabling system using constraint programming. The target problem has 26 constraints in total, and they are expressed as 24 constraints and an objective function in constraint programming. Currently, we are making a timetable through this system and applying the result to the actual class. Members' satisfaction is also much higher than manual results. We expect this paper can be a guide for making an automated course timetabling system.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.219-227
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• 2008

As found in research on constraint satisfaction problems, the choice of variable ordering heuristics is crucial for effective solving of constraint optimization problems. For the special problems such as energy-efficient clustering in heterogeneous wireless sensor networks, in which cluster heads have an inclination to be near a base station, we propose a new approach based on the static preferences variable orderings and provide a pnode heuristic algorithm for a specific application. The pnode algorithm selects the next variable with the highest Preference. In our problem, the preference becomes higher when the cluster heads are closer to the optimal region, which can be obtained a Priori due to the characteristic of the problem. Since cluster heads are the most dominant sources of Power consumption in the cluster-based sensor networks, we seek to minimize energy consumption by minimizing the maximum energy dissipation at each cluster heads as well as sensor nodes. Simulation results indicate that the proposed approach is more efficient than other methods for solving constraint optimization problems with static preferences.

• Journal of the Korea Computer Industry Society
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• v.8 no.2
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• pp.89-96
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• 2007

The object-based reservation scheduling techniques are to solve complex scheduling problems using constraint satisfaction problems and object-oriented concepts. We have tried to apply the object-based reservation scheduling techniques to the flight operation scheduling problems. For crew's satisfaction, we have considered the total crew's preferences board in the flight operation scheduling. To consider the over all satisfaction, the events of every object are alloted to the board along its priority. Constraints to reservation scheduling are classified to global and local. The definition of board and information of every event are global constraints and the preferences to object's board slots are local constraints. Actually, we have made an experiment on flight operation scheduling in order to raise crew's satisfaction.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.51-57
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• 2008

We present a modeling of constraint satisfaction problems and provide heuristic algorithms of backtracking search to optimize the frequency assignment. Our research objective is to find a frequency assignment that satisfies all the constraints using minimum number of frequencies while maximizing the number of community radio stations served for a given area. In order to get a effective solution, some ordering heuristics such as variable orderings and value orderings are provided to minimize the backtracking in finding all solutions within a limited time. To complement the late detection of inconsistency in the backtracking, we provide the consistency enforcing technique or constraint propagation to eliminate the values that are inconsistent with some constraints. By integrating backtracking search algorithms with consistency enforcing techniques, it is possible to obtain more powerful and effective algorithms of constraint satisfaction problems. We also provide the performance evaluation of proposed algorithms by comparing the theoretical lower bound and our computed solution.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.47-55
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• 2010

Linear constraint satisfaction optimization problem is a kind of combinatorial optimization problem involving linearly expressed objective function and complex constraints. Integer programming is known as a very effective technique for such problem but require very much time and memory until finding a suboptimal solution. In this paper, we propose a method to improve the search performance by integrating local search and integer programming. Basically, simple hill-climbing search, which is the simplest form of local search, is used to solve the given problem and integer programming is applied to generate a neighbor solution. In addition, constraint programming is used to generate an initial solution. Through the experimental results using N-Queens maximization problems, we confirmed that the proposed method can produce far better solutions than any other search methods.

• Information Systems Review
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• v.5 no.2
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• pp.203-217
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• 2003

Constraint Programming and Optimization have developed in different fields to solve common problems in real world. In particular, constraint propagation and linear Programming are their own fundamental and complementary techniques with the potential for integration to benefit each other. This intersection has evoked the efforts to combine both for a solution method to combinatorial optimization problems. Attempts to combine them have mainly focused on incorporating either technique into the framework of the other with traditional models left intact. This paper argues that integrating both techniques into an old modeling fame loses advantages from another and the integration should be molded in a new framework to be able to exploit advantages from both. The paper propose a declarative modeling framework in which the structure of the constraints indicates how constraint programming and optimization solvers can interact to solve problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.315-315
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• 1996