• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.50-59
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• 2014

In this paper, we develop an efficient approach to solve a multiple-item budget-constraint newsboy problem with a reservation policy. A conventional approach for solving such problem utilizes an approximation for the evaluation of an inverse of a Gaussian cumulative density function when the argument of the function is small, and a heuristic method for finding an optimal Lagrangian multiplier. In contrast to the conventional approach, this paper proposes more accurate method of evaluating the function by using the normalization and an effective numerical integration method. We also propose an efficient way to find an optimal Lagrangian multiplier by proving that the equation for the budget-constraint is in fact a monotonically increasing function in the Lagrangian multiplier. Numerical examples are tested to show the performance of the proposed approach with emphases on the behaviors of the inverse of a Gaussian cumulative density function and the Lagrangian multiplier. By using sensitivity analysis of different budget constraints, we show that the reservation policy indeed provides greater expected profit than the classical model of not having the reservation policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4814-4832
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• 2019

Plagiarism detection is increasingly exploiting text alignment. Text alignment involves extracting the plagiarism passages in a pair of the suspicious document and its source document. The heuristics have achieved excellent performance in text alignment. However, the further improvements of the heuristic methods mainly depends more on the experiences of experts, which makes the heuristics lack of the abilities for continuous improvements. To address this problem, machine learning maybe a proper way. Considering the position relations and the context of text segments pairs, we formalize the text alignment task as a problem of sequence labeling, improving the current methods at the model level. Especially, this paper proposes to use the probabilistic graphical model to tag the observed sequence of pairs of text segments. Hence we present the sequence labeling approach for text alignment in plagiarism detection based on Conditional Random Fields. The proposed approach is evaluated on the PAN@CLEF 2012 artificial high obfuscation plagiarism corpus and the simulated paraphrase plagiarism corpus, and compared with the methods achieved the best performance in PAN@CLEF 2012, 2013 and 2014. Experimental results demonstrate that the proposed approach significantly outperforms the state of the art methods.

• Nuclear Engineering and Technology
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• v.41 no.5
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• pp.747-752
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• 2009

A vulnerability assessment is essential for the efficient operation of a physical protection system (PPS). Previous assessment codes have used a simple model called an adversary sequence diagram. In this study, the use of a two-dimensional (2D) map of a facility as a model for a PPS is suggested as an alternative approach. The analysis of a 2D model, however, consumes a lot of time. Accordingly, a generalized heuristic algorithm has been applied to address this issue. The proposed assessment method was implemented to a computer code; Systematic Analysis of physical Protection Effectiveness (SAPE). This code was applied to a variety of facilities and evaluated for feasibility by applying it to various facilities. To help upgrade a PPS, a sensitivity analysis of all protection elements along a chosen path is proposed. SAPE will help to accurately and intuitively assess a PPS.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.159-168
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• 2020

The cryptocurrency market has received immense consideration in media and academia since the beginning of 2013 because of its huge price fluctuation. This study focuses on Arab investors who invest in the cryptocurrency market by investigating the influence of behavioral finance factors on investment decisions in the cryptocurrency market. A quantitative approach was used by employing a snowball sampling method through 112 questionnaires. The results show that herding theory, prospect theory, and heuristic theory have a significant effect on investors' investment decisions in the cryptocurrency market. This emphasizes the significant role of the proposed behavioral factors as determinants of the investors' investment decisions. This study contributes to the existing research by consolidating the results of different researches in this study. It also contributes to the investors' understanding of the dynamics of the cryptocurrency market and it enhances the ability to make informed decisions based on their understanding. The implication of the findings will prepare hit and run investors to be progressively prepared to stay in the cryptocurrency market and develop their abilities on the most proficient method to settle on sound venture choices. Furthermore, the findings of this study will encourage financial specialists to realize that information on the traditional finance theory is not adequate to excel in the cryptocurrency market.

• Smart Structures and Systems
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• v.20 no.1
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• pp.99-114
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• 2017

In cognitive science, it is illustrated how the collective opinions of a group of individuals answers to questions involving quantity estimation. One example of this approach is introduced in this article as Star Graph (SG) algorithm. This graph describes the details of communication among individuals to share their information and make a new decision. A new labyrinthine network of neighbors is defined in the decision-making process of the algorithm. In order to prevent getting trapped in local optima, the neighboring networks are regenerated in each iteration of the algorithm. In this algorithm, the normal distribution is utilized for a group of agents with the best results (guidance group) to replace the existing infeasible solutions. Here, some new functions are introduced to provide a high convergence for the method. These functions not only increase the local and global search capabilities but also require less computational effort. Various benchmark functions and engineering problems are examined and the results are compared with those of some other algorithms to show the capability and performance of the presented method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1564-1574
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• 1999

In order to improve the efficiency of optimizing compilers, integration of register allocation and instruction scheduling has been extensively studied. One of the promising integration techniques is register allocation based on register-reuse chains. However, the generation of register-reuse chains in the previous approach was not completely systematic and consequently it creates unnecessarily dependencies that restrict instruction scheduling. This paper proposes a new register allocation technique based on a systematic generation of register-reuse chains. The first phase of the proposed technique is to generate register-reuse chains that are optimal in the sense that no additional dependencies are created. Thus, register allocation can be done without restricting instruction scheduling. For the case when the optimal register-reuse chains require more than available registers, the second phase reduces the number of required registers by merging the register-reuse chains. Chain merging always generates additional dependencies and consequently enforces the execution order of instructions. A heuristic is developed for the second phase in order to reduce additional dependencies created by merging chains. For matrix multiplication program, the number of registers resulting from the first phase is small enough to fit into available registers for most basic blocks. In addition, it is shown that the restriction to instruction scheduling is reduced by the proposed merging heuristic of the second phase.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.396-401
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• 2002

The purpose of this 3-D numerical simulation is evaluate the application of a commercial CFD code to predict 3-D flow characteristics of wind turbine. The experimental approach, which has been main method of investigation, appears to be its limits, the cost increasing disproportionally with the size of the wind turbines, and is hence mostly limited to observing the phenomena. Hence, the use of Computational Fluid Dynamics (CFD) techniques and Wavier-Stokes solvers are considered a very serious contender. The flow solver CFX-TASCflow is employed in all computations presented in this paper. The 3-D flow separation and the wake distribution of 2 bladed Horizontal Axis Wind Turbines (HAWTs) are compared to Heuristic model and visualized result by NREL(National Renewable Energy Laboratory). Simulated 3-D flow separation structure on the rotor blade is very similar to Heuristic model and the wake structure of the wind turbine is good agree with visualized results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.34-39
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• 2008

Nash Equilibrium(NE) is essential to investigate a participant's bidding strategy in a competitive electricity market. Congestion on a transmission line makes it difficult to compute the NE due to causing a mixed strategy. In order to compute the NE of a multi-player game, some heuristics are proposed with concepts of a key player and power transfer distribution factor in other studies. However, generation capacity constraints are not considered and make it more difficult to compute the NE in the heuristics approach. This paper addresses an effect of generation capacity limits on the NE, and suggest a solution technique for the mixed strategy NE including generation capacity constraints as two heuristic rules. It is reported in this paper that a role of the key player who controls congestion in a NE can be transferred to other player depending on the generation capacity of the key player. The suggested heuristic rules are verified to compute the mixed strategy NE with a consideration of generation capacity constraints, and the effect of the generation constraints on the mixed strategy NE is analyzed in simulations of IEEE 30 bus systems.

• IE interfaces
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• v.16 no.3
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• pp.332-343
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• 2003

This paper deals with pre-erection scheduling and erection scheduling in shipbuilding. Among shipbuilding scheduling, the ship erection scheduling in a dock is one of the most important since the dock is the most critical resource in a shipyard. However, it is more reasonable to consider pre-erection scheduling and erection scheduling as unified because they compete with the common constrained resources such as labor, crane, space, and so on. It is very hard to consider two scheduling problems simultaneously, and hence, we approach them sequentially. At first, we propose space resource leveling heuristics in pre-erection scheduling given erection date. And then, considering the manpower resource determined by pre-erection scheduling, we also propose manpower resource leveling heuristics in erection scheduling. Various experimental results with real world data show that the proposed heuristics have good performance in terms of scheduling quality and time.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.52-59
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• 2008

This paper describes the secant method for solving the economic dispatch (ED) problem with generator constraints and transmission losses. The ED problem is an important optimization problem in the economic operation of a power system. The proposed algorithm involves selection of minimum and maximum incremental costs (lambda values) and then the evaluation of optimal lambda at required power demand is done by secant method. The proposed algorithm has been tested on a power system having 6, 15, and 40 generating units. Studies have been made on the proposed method to solve the ED problem by taking 120 and 200 units with generator constraints. Simulation results of the proposed approach were compared in terms of solution quality, convergence characteristics, and computation efficiency with conventional methods such as lambda iterative method, heuristic methods such as genetic algorithm, and meta-heuristic methods like particle swarm optimization. It is observed from different case studies that the proposed method provides qualitative solutions with less computational time compared to various methods available in the literature.