• Journal of Korea Society of Digital Industry and Information Management
• /
• v.17 no.3
• /
• pp.27-37
• /
• 2021

Highly informative heuristics in AI planning can help to a more efficient search a solutions. However, in general, to obtain informative heuristics from planning problem specifications requires a lot of computational effort. To address this problem, we propose a Partial Planning Graph(PPG) and Mixed Heuristics for solving planning problems more efficiently. The PPG is an improved graph to be applied to can find a partial heuristic value for each goal condition from the relaxed planning graph which is a means to get heuristics to solve planning problems. Mixed Heuristics using PPG requires size of each graph is relatively small and less computational effort as a partial plan generated for each goal condition compared to the existing planning graph. Mixed Heuristics using PPG can find partial interactions for each goal conditions in an effective way, then consider them in order to estimate the goal state heuristics. Therefore Mixed Heuristics can not only find interactions for each goal conditions more less computational effort, but also have high accuracy of heuristics than the existing max and additive heuristics. In this paper, we present the PPG and the algorithm for computing Mixed Heuristics, and then explain analysis to accuracy and the efficiency of the Mixed Heuristics.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.13 no.2
• /
• pp.27-34
• /
• 2017

Highly informative admissible heuristics can help to conduct more efficient search for optimal solutions. However, in general, more informative ones of heuristics from planning problems requires lots of computational effort. To address this problem, we propose an Delete Relaxation based Action Costs-based Planning Graph(ACPG) and Action Costs-based Heuristics for solving optimal planning problems more efficiently. The ACPG is an extended one to be applied to can find action costs between subgoal & goal conditions from the Relaxed Planning Graph(RPG) which is a common means to get heuristics for solving the planning problems, Action Costs-based Heuristics utilizing ACPG can find action costs difference between subgoal & goal conditions in an effective way, and then consider them to estimate the goal distance. In this paper, we present the heuristics algorithm to compute Action Costs-based Heuristics, and then explain experimental analysis to investigate the efficiency and the accuracy of the Action Costs-based Heuristics.

• The Journal of Korean Institute for Practical Engineering Education
• /
• v.3 no.1
• /
• pp.62-68
• /
• 2011

Usability heuristics("heuristics") are general principles for usability evaluation during user interface design. This method is commonly used by Human Computer Interaction(HCI) professionals; however, the most widely used set of heuristics which were originally created by Nielsen has not yet been found practical in the current state of Korean technologies. In our prior research, we found that some of Nielsen's heuristics are difficult for some evaluators to understand and insufficient to fully evaluate Korean applications, due to the broad-applicability of these heuristics and differences in cultural context. Therefore, in this study, professionals in computer science and related fields evaluated Nielsen's ten usability heuristics in order to gather logical bases for finding areas for improvement. The results of this study will help creating a new set of heuristics that will better valuate more recently developed applications.

• Journal of Distribution Science
• /
• v.21 no.9
• /
• pp.103-114
• /
• 2023

Purpose: This paper aims to assess psychological heuristics' effectiveness on cumulative returns after significant stock price changes. Specifically, it compares availability and anchoring heuristics' empirical validity due to conflicting stock return predictions. Research Design, Data, and Methodology: This paper analyzes stock price changes of Korean distribution industry stocks in the KOSPI market from January 2004 to July 2022, where daily fluctuations exceed 10%. It evaluates availability heuristics using daily KOSPI index changes and tests anchoring heuristics using 52-week high and low stock prices as reference points. Results: As a result of the empirical analysis, stock price reversals did not consistently appear alongside changes in the daily KOSPI index. By contrast, stock price drifts consistently appeared around the 52-week highest stock price and 52-week lowest stock price. The result of the multiple regression analysis which controlled for both company-specific and event-specific variables supported the anchoring heuristics. Conclusions: For stocks related to the Korean distribution industry in the KOSPI market, the anchoring heuristics theory provides a consistent explanation for stock returns after large-scale stock price fluctuations that initially appear to be random movements.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.9
• /
• pp.6290-6296
• /
• 2015

More informative ones of heuristics can help to conduct search more efficiently to obtain solution plan. However, in general, to derive highly informative heuristics from problem specifications requires lots of computational effort. To address this problem, we propose an State-Action based Planning Graph(SAPG) and Action-based heuristics for solving planning problems more efficiently. The SAPG is an extended one to be applied to can find interactions between subgoal & goal conditions from the relaxed planning graph which is a common means to get heuristics for solving the planning problems, Action-based heuristics utilizing SAPG graphs can find interactions between subgoal & goal conditions in an effective way, and then consider them to estimate the goal distance. Therefore Action-based heuristics have more information than the existing max and additive heuristics, also requires less computational effort than the existing overlap heuristics. In this pager. we present the algorithm to compute Action-based heuristics, and then explain empirical analysis to investigate the accuracy and the efficiency of the Action-based heuristics.

• Journal of Distribution Science
• /
• v.17 no.10
• /
• pp.73-81
• /
• 2019

Purpose - The purpose of this study was to examine the effect of the heuristic type of consumers affecting purchase decision making and the intention of shopping value in their relationship to derive mobile social commerce purchase promotion plans. Research design, data, and methodology - A research model was constructed to relate the mediating effect of shopping value between heuristic types and purchase intentions. A total of 233 valid questionnaires were used for analysis for users using mobile social commerce. The statistical program used SPSS 24.0 and AMOS 24.0, and correlation analysis, regression analysis, and 3-step parametric regression analysis were used for the analysis. Results - The results of the analysis showed that representativeness heuristics, availability heuristics, adjustment heuristics, and affect heuristics had a statistically significant effect on the utilitarian value and the hedonic value. On the other hand, affect heuristics among the heuristic types were found to have the greatest influence not only on the utilitarian value but also on the hedonic value. The two types of shopping value were found to be partially mediated between representativeness heuristics and purchase intentions, between adjustment heuristics and purchase intentions, and fully mediated between availability heuristics and purchase intentions, affect heuristics and purchase intentions. Conclusions - These findings suggest that mobile social commerce companies should check in advance how consumer heuristic types affect purchase intentions. In particular, affect heuristics are caused by consumers' emotional mood such as mood or external stimulus being more important to decision making than rational decision making. Therefore, the result of this study suggests that it can be an important factor to secure the competitiveness that the potential customers who access to use mobile social commerce can feel enough fun and enjoyment in the platform provided by the company. It is also worth paying attention to the utilitarian and hedonic values perceived by consumers. This is because the judgment regarding the economic, convenience and important information provided by the mobile social commerce users affects the purchase intention through the trust of the information, past use, and shopping experience displayed on the mobile social commerce platform.

• The Journal of Korean Institute for Practical Engineering Education
• /
• v.2 no.2
• /
• pp.165-171
• /
• 2010

Usability heuristics("heuristics") are general principles for usability evaluation during user interface design. Our ultimate goal is to extend the practice of usability evaluation methods to a wider audience(e.g. user interface designers and engineers) than Human Computer Interaction(HCI) professionals. To this end, we explored the degree to which Jakob Nielsen's ten usability heuristics are understood by professors and students in design and computer engineering. None of the subjects received formal training in HCI, though some may have had an awareness of some HCI principles. The study identified easy-to-understand heuristics, examined the reasons for the ambiguities in others, and discovered differences between the responses of professors and students to the heuristics. In the course of the study, the subjects showed an increased tendency to think in terms of user-centric design. Furthermore, the findings in this study offer suggestions for improving these heuristics to resolve ambiguities and to extend their practice for user interface designers and engineers.

• Journal of Korean Society for Quality Management
• /
• v.17 no.2
• /
• pp.121-141
• /
• 1989

This paper is concerned with a development and evaluation of heuristics for the multi-stage sequence dependent flowshop sequencing. Eighteen heuristics, CAM1, CAM2, and etc., are proposed. The performance measure is a makespan which is to be minimized. The experiment for each algorithm is designed for a 4*3*3 factorial design with 360 observations. The experimental factors are PS(ratio of processing times to setup times), M(number of machines), N(number of jobs). The makespan of the proposed heuristics is compared with the optimal makespan obtained by the complete enumeration of schedules. This yardstick of comparison is called a relative error. The mean relative errors of the eighteen heuristics are from 2.048% to 8.717%. The computational results are analysed using SPSS. The experimental results show that the three factors are statistically significant at 5% level. The simulation for the large size problems is conducted to show having the similar computational results like the small size problems.

• Industrial Engineering and Management Systems
• /
• v.8 no.4
• /
• pp.213-220
• /
• 2009

A revenue sharing contract is one of the mechanisms that coordinate decision makers in a decentralized supply chain toward the consensual goal. The transfer prices between different echelons in the supply chain influence the total supply chain profits. The study aims to explore various transfer pricing heuristics on the supply chain coordination in terms of the supply chain profits and their interactions with the revenue sharing rate. A model is proposed for formulating the collaborative production and distribution planning in a decentralized supply chain with the revenue sharing mechanism. Experiment results indicate that the transfer price and the revenue sharing rate affect significantly the coordination. Among the studied pricing heuristics, the variable-cost pricing method led to the best SC profits. Raising the revenue sharing rate reduced the SC profits no matter what heuristics were employed. Furthermore, the experiments provide us clues for finding the optimal transfer price for the supply chain.

• Journal of Korean Institute of Industrial Engineers
• /
• v.11 no.2
• /
• pp.57-73
• /
• 1985

Group scheduling problem in a multi-stage manufacturing system is reviewed and two heuristic procedures for minimizing the makespan are developed by employing the methods of flow shop sequencing heuristics with a slight modification. The comparisons among the five heuristics, three previously reported heuristics and two heuristics suggested by this study, are made on different problem sizes. The computational results indicate that NEH-GS method gives better group schedules than the other heuristics tested, but its computation time increases rapidly as the problem size increases. On the other hand, CDS-GS method provides relatively good group schedules with less computation time compared with NEH-GS method.