• Journal of Korea Port Economic Association
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• v.29 no.3
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• pp.159-174
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• 2013

This paper mainly deals with the appropriation of ship voyage allocation, using a heuristic regression model, in order to reduce total costs incurred in port, yard and at sea under the specific port condition. Because of different behavior of costs incurred in port, yard and at sea, an effort to minimize these costs by adjusting the number of voyages for three ship classes(50,000, 100,000, and 150,000-ton) should be made. For instance, if the port managers attempt to reduce the sea transport cost by increasing the annual allocated number of ship voyages classed 150,000-ton for economies of scale, they have no choice but to suffer a significant increase in queueing cost due to port congestion. To put it differently, there are trade-off relationships among the costs incurred in port, yard, and at sea. We utilized a computer simulation result to perform a couple of regression analyses in order to figure out the appropriate range of allocated number of voyages of each ship class using a heuristic approach. The detailed analytical results will be shown at the main paper. We also suggested a net present value(NPV) model to make a proper investment decision for an additional berth of 200,000-ton class that alleviates port congestion and reduces transport cost incurred both in port and at sea.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.203-210
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• 2014

This study proposes adaptive decision making method having feed-back structure of regression and simulation models to support the quick decision making of production managers by managing and integrating the mutual relationship among historical data. For that, from historical data that have extracted and accumulated from each process, we first selected major constraint resources that are used as independent variables in regression model. The regression model is designed by using the dependent variables (objectives) that defined above by managers and independent variables selected in previous step and simulation model that are composed of constraint resources is designed. In process of simulation run, we obtain the multiple feasible solutions (alternatives) by using meta-heuristic method. Each solution is substituted by regression equation and we found the optimal solution that is minimum of difference between values obtained by regression model and simulation results. The optimal solution is delivered and incorporated to production site and current operation results from production site is used to generate new regression model after that time.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.533-544
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• 2007

사례 기반 계획 시스템은 과거의 유사한 사례 계획들을 이용함으로써 새로운 문제를 위한 계획을 효율적으로 생성할 수 있다. 하지만 대부분의 기존 사�� 기반 계획 시스템들은 사례 검색 및 사례 일반화를 위한 제한적 기능들만을 제공할 뿐만 아니라, 계획 생성과정에 사용자 참여를 허용하지 않는다. 이러한 문제점들을 극복하기 위해, 본 논문에서는 새로운 사례 기반 계획시스템인 JCBP를 제안한다. 본 논문에서는 먼저 JCBP 시스템의 설계와 구현에 대해 설명하고, 실험을 통해 JCBP시스템의 성능을 분석한다. JCBP 시스템은 효율적인 메모리 사용과 사례 검색을 위해 각 도메인의 동일한 작업목표를 가진 사례들을 개별 사례베이스로 그룹화하고, 이들에 대한 색인들을 유지한다. 도 이 시스템은 문제모델로부터 자동으로 추출한 휴리스틱 지식을 사례 검색과 적응 단계에 이용하며, 목표 회귀를 통한 사례 일반화 기능을 제공한다. 또한 JCBP 시스템은 대화형 모드를 통해 혼합 주도 계획 생성 기능을 제공한다. 따라서 사용자의 지식과 선호도를 이용할 수 있어, 계획 생성의 복잡도를 줄이고 사용자의 만족도를 높일 수 있다.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.147-159
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• 2023

This study is a study to develop a model for measurement and processing of experience data, which is emerging as a core value in quality management of medical services. In the theoretical background, a literature study was conducted on the importance of experience in medical service, measurement and processing of experience data, and realization of patient-centeredness. Based on these literature and theoretical background research results, operational definitions were performed for the following four research variables, and statistical tests were conducted. Hypothesis 1 is the effect of measuring experience data from the perspective of three factors on persona modeling, Hypothesis 2 is the effect of persona modeling on service blueprint visualization, Hypothesis 3 is the effect of service blueprint visualization on realization of patient-centeredness, and Hypothesis 4 is persona modeling This is the effect that modeling has on the realization of patient-centeredness. After data-based testing of factor analysis, reliability analysis, and correlation analysis, all four hypotheses were adopted as a result of verification using regression analysis. In conclusion, in an era where it is difficult to recognize the value of having only good medical staff and medical equipment in hospitals, it was possible to grasp the meaning that what kind of medical service experience is continuously obtained is more important to patients than the effectiveness of medical staff and medical equipment. In the era of the service economy, the core of hospital service competitiveness is providing attractive experiences, which is the real strength of hospitals, so the measurement and processing of experience data, which is the subject of this study, will have an important meaning in realizing patient-centeredness and realizing smart hospitals.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.