• Journal of the Korean Society of Industry Convergence
• /
• v.27 no.2_2
• /
• pp.467-473
• /
• 2024

Metaheuristics' impact is profound across many fields, yet domestic financial portfolio optimization research falls short, particularly in asset allocation. This study delves into metaheuristics for portfolio optimization, examining theoretical and practical benefits. Findings indicate portfolios optimized via metaheuristics outperform the Dow Jones Index in Sharpe ratios, underscoring their potential to enhance risk-adjusted returns significantly. Tabu search, in comparison to Simulated Annealing, demonstrates superior performance by efficiently navigating the search space. Despite these advancements, practical application remains challenging due to the complexities in metaheuristic implementation. The study advocates for broader algorithmic exploration, including population-based metaheuristics, to refine asset allocation strategies further. This research marks a step towards optimizing portfolios from an extensive array of financial assets, aiming for maximum efficacy in investment outcomes.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.3
• /
• pp.18-27
• /
• 2009

In this paper, we propose a frame rate conversion algorithm using adaptive search-based motion estimation (ME). The proposed ME method uses recursive search, 3-step search, and single predicted search as candidates for search strategy. The best method among the three candidates is adaptively selected on a block basis according to the predicted motion type. The adaptation of the search method improves the accuracy of the estimated motion vectors while curbing the increase of computational load. To support the proposed ME method, an entire image is divided into three regions with different motion types. Experimental results show that the proposed FRC method achieves better image quality than existing algorithms in both subjective and objective measures.

• Journal of Broadcast Engineering
• /
• v.16 no.4
• /
• pp.647-656
• /
• 2011

Motion estimation using one-bit transform and two-bit transform reduces the complexity for computation of matching error; however, the peak signal-to-noise ratio (PSNR) is degraded. Modified 1BT (M1BT) and modified 2BT (M2BT) have been proposed to compensate degraded PSNR by adding conditional local search. However, these algorithms require many additional search points in fast moving sequences with a block size of $16{\times}16$. This paper provides more efficient search method by preparing candidate blocks using the number of non-matching points (NNMP) than the conditional local search. With this NNMP-based search, we can easily obtain candidate blocks with small NNMP and efficiently search final motion vector. Experimental results show that the proposed algorithm not only reduces computational complexity, but also improves PSNR on average compared with conventional search algorithm used in M1BT, M2BT and AM2BT.

• Journal of Integrative Natural Science
• /
• v.3 no.3
• /
• pp.143-147
• /
• 2010

Since it is of great importance to know how a ligand binds to a receptor, there have been a lot of efforts to improve the quality of prediction of docking poses. Earlier efforts were focused on improving search algorithm and scoring function in a docking program resulting in a partial improvement with a lot of variations. Although these are basically very important and essential, more tangible improvements came from the reduction of search space. In a normal docking study, the approximate active site is assumed to be known. After defining active site, scoring functions and search algorithms are used to locate the expected binding pose within this search space. A good search algorithm will sample wisely toward the correct binding pose. By careful study of receptor structure, it was possible to prioritize sub-space in the active site using "receptor-based pharmacophores" or "hot spots". In a sense, these techniques reduce the search space from the beginning. Further improvements were made when the bound ligand structure is available, i.e., the searching could be directed by molecular similarity using ligand information. This could be very helpful to increase the accuracy of binding pose. In addition, if the biological activity data is available, docking program could be improved to the level of being useful in affinity prediction for a series of congeneric ligands. Since the number of co-crystal structures is increasing in protein databank, "Ligand-Guided Docking" to reduce the search space would be more important to improve the accuracy of docking pose prediction and the efficiency of virtual screening. Further improvements in this area would be useful to produce more reliable docking programs.

• The Journal of Korean Association of Computer Education
• /
• v.13 no.1
• /
• pp.45-52
• /
• 2010

With rapid increase in the number of web documents, the problem of information overload in Internet search is growing seriously. In order to improve web search results, previous research studies employed user queries/preferred words and the number of links in the web documents. In this study, performance of the search results exploiting these two criteria is examined and other preference criteria for web documents are analyzed. Experimental results show that personalized web search results employing queries and preferred words yield up to 1.7 times better performance over the current search engine and that the search results using the number of links gives up to 1.3 times better performance. Although it is found that the first of the user's preference criteria for web documents is the contents of the document, readability and images in the document are also given a large weight. Therefore, performance of web search personalization algorithms will be greatly improved if they incorporate objective data reflecting each user's characteristics in addition to the number of queries and preferred words.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.2
• /
• pp.78-84
• /
• 2009

In general video coding systems, motion estimation (ME) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. Fractional pixel motion estimation can improve the video compression rate at the cost of higher computational complexity. It is based on the experimental results that the sum of absolute differences (SAD) shows parabolic shape and thus can be approximated by using interpolation technique. In this paper, we propose a fast fractional pixel search algorithm by combining SASR (Simplified Adaptive Search Range) and the CBCDS (Center Biased Cross-Diamond Search) pattern with the predicted motion vector. Compare with the fractional pel full search and the CBFPS, the proposed CBCDS algorithms can reduce fractional pel search points up to 81.4%, respectively with the PSNR lost about 0.05dB.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.9
• /
• pp.85-91
• /
• 2013

This paper proposes the data reusable search scan methods for full search and fast search to implement low power Motion Estimation (ME). The proposed Optimized Sub-region Partitioning (OSP) method which divide search region into several sub-region can reduce the number of the required Reconfigurable Register Array (RRA) by half compared to the existing smart snake scan method for the same data reusability. In addition, the proposed Center Biased Search Scan method (CBSS) for various fast search algorithms can improve the data reusability. The performance comparisons show that the proposed search scan methods can reduce the average redundant data loading about 26.9% and 16.1% compared with the existing rater scan and snake scan methods, respectively. Due to the reduction of memory accesses, the proposed search scan methods are quite suitable for low power and high performance ME implementation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.2B
• /
• pp.71-79
• /
• 2006

Address lookup is an essential function in the Internet routers, and it determines overall router performance. In this paper, we have thoroughly investigated the binary-search-based address lookup algorithms and proposed a new algorithm based on binary search on prefix lengths. Most of the existing binary search schemes perform binary search on prefix values, and hence the lookup speed is proportional to the length of prefixes or the log function of the number of prefixes. The previous algorithm based on binary search on prefix lengths has superior lookup performance than others. However, the algorithm requires very complicated pre-computation of markers and best matching prefixes in internal nodes since naive binary search is not possible in their scheme. This complicated pre-computation makes the composition of the routing table and incremental update very difficult. By using leaf-pushing, the proposed algorithm in this paper removes the complicated pre-computation of the Previous work in performing the binary search on prefix lengths. The performance evaluation results show that the proposed scheme has very good performance in lookup speed compared with previous works.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.11
• /
• pp.2298-2304
• /
• 2015

In this paper, we provide a new approach which optimizes the vertical tilting angle of the base station for multi-cell multiple-input single-output (MISO) downlink active antenna systems (AAS). Instead of the conventional optimal algorithm which requires an exhaustive search, we propose simple and near optimal algorithms. First, we represent a large system approximation based vertical beamforming algorithm which is applied to the average sum rate by using the random matrix theory. Next, we suggest a signal-to-leakage-and-noise ratio (SLNR) based vertical beamforming algorithm which simplifies the optimization problem considerably. In the simulation results, we demonstrate that the performance of the proposed algorithms is near close to the exhaustive search algorithm with substantially reduced complexity.

• Journal of Korean Society of Transportation
• /
• v.14 no.1
• /
• pp.51-67
• /
• 1996

The optimal path-finding problem becomes complicated when multiple variables are simultaneously considered such as physical route length, degree of congestion, traffic capacity of intersections, number of intersections and lanes, and existence of free ways. Therefore, many researchers in various fields (management science, computer science, applied mathematics, production planning, satellite launching) attempted to solve the problem by ignoring many variables for problem simplification, by developing intelligent algorithms, or by developing high-speed hardware. In this research, an integration of expert system technique and case-based reasoning in high level with a conventional algorithms in lower level was attempted to develop an optimal path-finding system. Early application of experienced driver's knowledge and case data accumulated in case base drastically reduces number of possible combinations of optimal paths by generating promising alternatives and by eliminating non-profitable alternatives. Then, employment of a conventional optimization algorithm provides faster search mechanisms than other methods such as bidirectional algorithm and $A^*$ algorithm. The conclusion obtained from repeated laboratory experiments with real traffic data in Seoul metropolitan area shows that the integrated approach to finding optimal paths with consideration of various real world constraints provides reasonable solution in a faster way than others.