• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.201-207
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• 2018

There is no known polynomial time algorithm for random-type quadratic assignment problem(RQAP) that is a NP-complete problem. Therefore the heuristic or meta-heuristic approach are solve the approximated solution for the RQAP within polynomial time. This paper suggests polynomial time algorithm for random type quadratic assignment problem (QAP) with time complexity of $O(n^2)$. The proposed algorithm applies one-to-one matching strategy between ascending order of sum of distance for each location and descending order of sum of quantity for each facility. Then, swap the facilities for reflect the correlation of distances of locations and quantities of facilities. For the experimental data, this algorithm, in spite of $O(n^2)$ polynomial time algorithm, can be improve the solution than genetic algorithm a kind of metaheuristic method.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.175-181
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• 2014

This paper suggests O(m) polynomial time heuristic algorithm to obtain the solution for the driver scheduling problem, DSP, that has been classified as NP-complete problem. The proposed algorithm gets the initial assignment of n minimum number of drivers from given m schedules. Nextly, this algorithm gets the minimum total time (TC) using 5 rules of swap and insert for decrease of over times (OT) and idle times (IT). Although this algorithm is a heuristic polynomial time algorithm with O(m) time complexity rules to be find a optimal (or approximate) solution, this algorithm is equal to metaheuristic methods for the 5 experimental data. To conclude, this paper shows the DSP is not NP-complete problem but Polynomial time (P)-problem with polynomial time rules.

• Journal of KIISE
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• v.42 no.3
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• pp.361-366
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• 2015

Gap parsing is an algorithm for parsing incomplete input strings which include some gaps. Gap parsing is different from conventional parsing, and as known results, one-gap parsing algorithms for arbitrary context-free grammar and LL(1) grammar have $O(n^3)$ and $O(n^2)$ time complexity, respectively. This paper presents a one-gap parsing algorithm for extended PLR(1) grammars. Extended PLR(1) grammars are the class of grammars smaller than LR(1) but much larger than LL(1). The one-gap parsing algorithm of the grammar class is shown to have the time complexity of $O(n^2)$, which is equal to the complexity of one-gap parsing algorithms for LL(1) grammars.

• ETRI Journal
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• v.43 no.3
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• pp.483-510
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• 2021

In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in O (N) time, whereas quantum algorithm design is based on Grover's method, which completes the search in $O(\sqrt{N})$ time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum-based combined exact (QBCE) algorithm for the pattern-matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing-based exact (QPBE) pattern-matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are $O(\sqrt{t})$ and $O(\sqrt{N})$, and the exceptional worst case is bounded by O (t) and O (N). Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern-matching methods.

• ETRI Journal
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• v.45 no.6
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• pp.996-1006
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• 2023

Renewable energy is promoted massively to overcome problems that fossil fuel power plants generate. One popular renewable energy type that offers easy installation is a photovoltaic (PV) system. However, the energy harvested through a PV system is not optimal because influenced by exposure to solar irradiance in the PV module, which is constantly changing caused by weather. The maximum power point tracking (MPPT) technique was developed to maximize the energy potential harvested from the PV system. This paper presents the MPPT technique, which is operated on a new high-gain voltage DC/DC converter that has never been tested before for the MPPT technique in PV systems. Fuzzy logic (FL) was used to operate the MPPT technique on the converter. Conventional and adaptive perturb and observe (P&O) techniques based on variables step size were also used to operate the MPPT. The performance generated by the FL algorithm outperformed conventional and variable step-size P&O. It is evident that the oscillation caused by the FL algorithm is more petite than variables step-size and conventional P&O. Furthermore, FL's tracking speed algorithm for tracking MPP is twice as fast as conventional P&O.

• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.565-575
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• 2013

Let H be a real Hilbert space and let T : H ${\rightarrow}$ H be a Lipschitz pseudocontractive mapping. We introduce a modified Ishikawa iterative algorithm and prove that if $F(T)=\{x{\in}H:Tx=x\}{\neq}{\emptyset}$, then our proposed iterative algorithm converges strongly to a fixed point of T. No compactness assumption is imposed on T and no further requirement is imposed on F(T).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.290-296
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• 2008

This paper considers a two-stage dynamic lot-sizing problem constrained by a supplier's production capacity. We derive an improved O($T^6$) algorithm over the O($T^7$) algorithm in van Hoesel et al. (2005).

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.340-345
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• 1994

Dynamic hybrid position/force control of flexible manipulators is proposed. First, a 2 D.O.F. flexible manipulator is modeled using the spring-mass model. Second, the equation of motion considering the tip constraints is derived. Third, hybrid position/force control algorithm is derived. In this control algorithm, the differentiable order of the desired trajectory and the stability condition are different from the case of rigid manipulators. Lastly, to verify the effectiveness of the proposed control algorithm, simulation results are presented.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.787-790
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• 1998

In this paper we consider strongly polynomial variations of the auction algorithm for the single origin/all destinations shortest path problem. These variations are based on the idea of graph reduction, that is, deleting unnecessary arcs of the graph by using certain bounds naturally obtained in the course of the algorithm. We study the structure of the reduced graph and we exploit this structure to obtain algorithm with O(n min{m, nlogn}) and O(n$^{2}$) running time.

• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.959-973
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• 2001

We shall discuss one of some techniques needed to analyze algorithms. It is called a big-O function technique. The measures of efficiency of an algorithm have two cases. One is the time used by a computer to solve the problem using this algorithm when the input values are of a specified size. The other one is the amount of computer memory required to implement the algorithm when the input values are of a specified size. Mainly, we will restrict our attention to time complexity. To figure out the Time Complexity in nonlinear problems of Numerical Analysis seems to be almost impossible.