• Journal of the Korean Society for information Management
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• v.12 no.1
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• pp.143-161
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• 1995

This paper defines online search strategy as a global approach to the resolution of online searching. Five search strategy models including Brief Search. Building Blocks Strategies. Successive Facet Strategies, Successive Fractions Approach, and Citation Pearl Growing, are critically reviewed. Applicability and adaptability of each strategy are examined in the real concrete online searching environment.

• Korean small business review
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• v.41 no.2
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• pp.1-24
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• 2019

This paper seeks to explore the effects of search strategies on innovation performance in the context of small and medium enterprises. The empirical results of 3,398 Korean SMEs demonstrate that there is a substitutive relationship between search depth and search width, and this substitutive relationship is weakened when a firm possesses collaboration experience. Furthermore, although these two types of search enhance innovation performance, the impact of search depth is greater than that of search width. The positive effect of search width on innovation performance is weakened when the firm adopts formal information protection mechanisms.

• Journal of KIISE
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• v.44 no.10
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• pp.1034-1044
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• 2017

Although traversal strategies are important for the performance of model checking, many studies have ignored the impact of traversal strategies in model checking with a block-encoded abstract reachability graph. Studies have considered traversal strategies only for an abstract reachability graph without block-encoding. Block encoding plays a crucial role in the model checking performance. This paper therefore describes Dual-traversal strategy, a simple and novel technique to control traversal strategies in a block-encoded abstract reachability graph. This method uses two traversal strategies for a model checking, one for effective block-encoding, and the other for traversal in an encoded abstract reachability graph. Dual-traversal strategy is very simple and can be implemented without overhead compared to the existing single-traversal strategy. We implemented the Dual-traversal strategy in an open source model checking tool and compare the performances of different traversal strategies. The results show that the model checking performance varies from the traversal strategies for the encoded abstract reachability graph.

• Journal of Information Management
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• v.26 no.1
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• pp.80-98
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• 1995

Search strategies is a means to make an efficient search. Among several studies of search strategy, Bates' $\ulcorner$Search Tactics$\lrcorner$ has been often cited and introduced, but their studies have been superficial. In this paper, the contents of Bates' $\ulcorner$Search Tactics$\lrcorner$ are examined in detail, and we try to represent the actual online search process based upon Bates' $\ulcorner$Search Tactics$\lrcorner$. The following three kinds of survey are made in order to clarify which and how tactics are used: (1) Interview with 7 searchers who belong to different types of organizations, and use different kinds of databases (2) Analysis of some online search records. (3) Analysis of written applications for a newspaper database during one year. In conclusion, Bates' tactics falls into categories and new several tactics which often used are added. The following five factors affect online search activities, search strategy, and search tactics. (1) the difficulty of search requests (2) the kinds of databases (3) the charging policy for each online search (4) the presence of the user during the search (5) the searcher' online experience In the limited condition, typical tactics are suggested, but in order to generalize the pattern of using tactics, further investigation is necessary.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.598-600
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• 2004

기존의 연구 논문 중 비결정론적인 알고리즘인 유전자 알고리즘이나 인공신경망 등을 오델로 게임에 적용하여 자동학습을 시킨 예는 많으나 면역알고리즘을 모델로 게임에 적용한 예는 찾기가 어렵다 본 논문에서는 생리학의 면역시스템의 특징을 그대로 적용한 면역알고리즘을 모델로 게임에 적용하여 게임전략 생성에 관하여 연구한다. 생리학의 면역시스템은 자기조절능력이 있다는 외과 재 감염시 빠르게 대응할 수 있다는 특징이 있다. 면역알고리즘을 이용하여 탐색된 전략을 유전자알고리즘 그리고 기존에 연구되어진 게임전략 등과 실험하여 그 결과를 비교.연구한 결과 면역알고리즘을 적용하여 탐색된 모델로 게임전략이 가장 높은 승률을 보인다.

• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.467-477
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• 2001

반응적 타부 탐색은 단순한 타부 탐색과 비교해서 중장기 메모리를 이용한 학습을 통하여 타부리스트의 크기를 반응적으로 변화시킴으로써 NP-hard 문제에 속하는 다양한 조합 최적해 문제에 대해서 좋은 해를 효율적으로 찾는다. 본 논문에서는 반응적 타부 탐색에 있어서 중장기 메모리를 이용한 탈출 메커니즘으로 이웃 해 전략 전환 메커니즘이라는 개념을 제시한다. 제시된 이웃 해 전략 전환 메커니즘을 이용한 반응적 타부 탐색을 특정 공과 대학의 강의 시간표 작성 문제와 외판원문제 (traveling salesman problem)에 적용하여 기존의 반응적 타부 탐색과 비교 분석을 하였다. 전산 실험 결과 제시된 알고리즘은 기존의 반응적 타부 탐색 알고리즘에 비교하여 더 좋은 해를 더 짧은 시간에 찾아주었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.650-656
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• 1999

In this paper, we study on the convergence of the evolution strategies by introducing the Lamarckian evolution and the Baldwin effect, and propose a random local searching and a reinforcement local searching methods. In the random local searching method some neighbors generated randomly from each individual are med without any other information, but in the reinforcement local searching method the previous results of the local search are reflected on the current local search. From the viewpoint of the purpose of the local search it is suitable that we try all the neighbors of the best individual and then search the neighbors of the best one of them repeatedly. Since the reinforcement local searching method based on the Lamarckian evolution and Baldwin effect does not search neighbors randomly, but searches the neighbors in the direction of the better fitness, it has advantages of fast convergence and an improvement on the global searching capability. In other words the performance of the evolution strategies is improved by introducing the learning, reinforcement local search, into the evolution. We study on the learning effect on evolution strategies by applying the proposed method to various function optimization problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.423-433
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• 2017

This study examines the effects of supply chain search and application strategies on organizational capability and corporate operational performance. To achieve this aim, a survey was administered to middle managers of 298 small- and medium-sized venture companies in Busan, South Korea. Empirical analysis showed that supply chain search and application strategies have a positive effect on organizational capability and corporate operational performance. In addition, organizational capability is positively mediated by supply chain search and application strategies in terms of the mediating effect of corporate operational performance. Consequently, search and application as supply chain strategies are facilitating factors as mediators that improve corporate performance through the concentration of organizational capability. Findings suggest that the search and application of supply chain strategies need to act as accelerating variables that improve organizational performance, and supply chain strategies need to be applied in small- and medium-sized manufacturing businesses.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.1-13
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• 2014

This study examines the relationship between firms' external search strategy and their innovation performance. In addition to revisiting the relationship between open search strategy and product innovation, we further extend the impact of use of external knowledge sources to process and organizational innovation. Using the 2010 Korean Innovation Survey (KIS) of manufacturing firms, we report that on average, venture firms search more widely (external search breadth) and deeply (external search depth) across a variety of external search channels than non-venture firms. We then further explore the impact of venture and non-venture firms' use of external search strategies on innovation performance. We find that both searching widely and deeply increase the likelihood of non-venture firm's successes in product, process and organizational innovation. Similar results can be found for the venture firm's success in organizational innovation. However, only searching deeply increases the likelihood of venture firms' success in product and process innovation.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.27-35
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• 2021

Local search has been used to solve various combinatorial optimization problems. One of the most important factors in local search is the method of generating a neighbor solution. In this paper, we propose neighbor generation strategies of local search for permutation-based combinatorial optimization, and compare the performance of each strategies targeting the traveling salesman problem. In this paper, we propose a total of 10 neighbor generation strategies. Basically, we propose 4 new strategies such as Rotation in addition to the 4 strategies such as Swap which have been widely used in the past. In addition, there are Combined1 and Combined2, which are made by combining basic neighbor generation strategies. The experiment was performed by applying the basic local search, but changing only the neighbor generation strategy. As a result of the experiment, it was confirmed that the performance difference is large according to the neighbor generation strategy, and also confirmed that the performance of Combined2 is the best. In addition, it was confirmed that Combined2 shows better performance than the existing local search methods.