• Journal of the Korea Society of Computer and Information
• /
• v.19 no.4
• /
• pp.91-99
• /
• 2014

TThis paper suggests an heuristic polynomial time algorithm to solve the optimal solution for QAP (quadratic assignment problem). While Hungarian algorithm is most commonly used for a linear assignment, there is no polynomial time algorithm for the QAP. The proposed algorithm derives a grid type layout among unit distances of a distance matrix. And, we apply max-flow/min-distance approach to assign this grid type layout in such a descending order way that the largest flow is matched to the smallest unit distance from flow matrix. Evidences from implementation results of the proposed algorithm on various numerical grid type QAP examples show that a solution to the QAP could be obtained by a polynomial algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.6
• /
• pp.211-220
• /
• 2013

This paper proposes an algorithm that easily finds an optimal solution for linear bottleneck assignment problems. It is either threshold or augmenting path algorithm that is generally used to solve the bottleneck assignment problem. This paper proposes a reverse-delete algorithm that follows 2 steps. Firstly, the algorithm deletes the maximum cost in a given matrix until it renders a single row or column. Next, the algorithm improves any solution that contains a cost exceeding the threshold value $c^*_{ij}$. Upon its application to 28 balanced assignment problems and 7 unbalanced problems, the algorithm is found to be both successful and simple.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.1
• /
• pp.1-20
• /
• 2018

Service composition in the Inter-Cloud raises new challenges that are caused by the different Quality of Service (QoS) requirements of the users, which are served by different geo-distributed Cloud providers. This paper aims to explore how to select and compose such services while considering how to reach high efficiency on cost and response time, low network latency, and high reliability across multiple Cloud providers. A new hybrid multi-objective evolutionary algorithm to perform the above task called LS-NSGA-II-DE is proposed, in which the differential evolution (DE) algorithm uses the adaptive mutation operator and crossover operator to replace the those of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to get the better convergence and diversity. At the same time, a Local Search (LS) method is performed for the Non-dominated solution set F{1} in each generation to improve the distribution of the F{1}. The simulation results show that our proposed algorithm performs well in terms of the solution distribution and convergence, and in addition, the optimality ability and scalability are better compared with those of the other algorithms.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.8
• /
• pp.135-143
• /
• 2003

This paper presents the impact minimization of a biped robot by using genetic algorithm. In case we want to accomplish the designed plan under the special environments, a robot will be required to have walking capability and patterns with legs, which are in a similar manner as the gaits of insects, dogs and human beings. In order to walk more effectively, studies of mobile robot movement are needed. To generate optimal motion for a biped robot, we employ genetic algorithm. Genetic algorithm is searching for technology that can look for solution from the whole district, and it is possible to search optimal solution from a fitness function that needs not to solve differential equation. In this paper, we generate trajectories of gait and trunk motion by using genetic algorithm. Using genetic algorithm not only on gait trajectory but also on trunk motion trajectory, we can obtain the smoothly stable motion of robot that has the least impact during the walk. All of the suggested motions of biped robot are investigated by simulations and verified through the real implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.4864-4882
• /
• 2016

In this work, we consider the optimization problem of minimizing energy consumption for real-time multicast over wireless multi-hop networks. Previously, a distributed primal-dual subgradient algorithm was used for finding a solution to the optimization problem. However, the traditional subgradient algorithms have drawbacks in terms of i) sensitivity to iteration parameters; ii) need for saving previous iteration results for computing the optimization results at the current iteration. To overcome these drawbacks, using a joint network coding and scheduling optimization framework, we propose a novel distributed primal-dual Random Deflected Subgradient (RDS) algorithm for solving the optimization problem. Furthermore, we derive the corresponding recursive formulas for the proposed RDS algorithm, which are useful for practical applications. In comparison with the traditional subgradient algorithms, the illustrated performance results show that the proposed RDS algorithm can achieve an improved optimal solution. Moreover, the proposed algorithm is stable and robust against the choice of parameter values used in the algorithm.

• Journal of Electrical Engineering and Technology
• /
• v.2 no.3
• /
• pp.312-319
• /
• 2007

The solution of the power flow is one of the most important problems in electrical power systems. These traditional methods such as Gauss-Seidel method and Newton-Raphson (NR) method have had drawbacks up to now such as initial values, abnormal operating solutions and divergences in heavy loads. In order to overcome theses problems, the power flow solution incorporating genetic algorithm (GA) is introduced in this paper. General operator of genetic algorithm, arithmetic crossover, and non-uniform mutation operator of GA are suggested to solve the power flow problem. While abnormal solution cannot be obtained by a NR method, multiple power flow solution can be obtained by a GA method. With a heavy load, both normal solution and abnormal solution can be obtained by a proposed method. In this paper, a floating number representation instead of the binary number representation is introduced for accuracy. Simulation results have been compared with traditional methods.

• Advances in Computational Design
• /
• v.5 no.3
• /
• pp.305-321
• /
• 2020

In this paper is presented the solution method for three-dimensional problem of transversely isotropic body's elastoplastic deformation by the finite element method (FEM). The process of problem solution consists of: determining the effective parameters of a transversely isotropic medium; construction of the finite element mesh of the body configuration, including the determination of the local minimum value of the tape width of non-zero coefficients of equation systems by using of front method; constructing of the stiffness matrix coefficients and load vector node components of the equation for an individual finite element's state according to the theory of small elastoplastic deformations for a transversely isotropic medium; the formation of a resolving symmetric-tape system of equations by summing of all state equations coefficients summing of all finite elements; solution of the system of symmetric-tape equations systems by means of the square root method; calculation of the body's elastoplastic stress-strain state by performing the iterative process of the initial stress method. For each problem solution stage, effective computational algorithms have been developed that reduce computational operations number by modifying existing solution methods and taking into account the matrix coefficients structure. As an example it is given, the problem solution of fibrous composite straining in the form of a rectangle with a system of circular holes.

• Nuclear Engineering and Technology
• /
• v.55 no.9
• /
• pp.3301-3312
• /
• 2023

This study incorporates a high-fidelity transient analysis solver based on multigroup CMFD in the MOC code STREAM. Transport modeling with heterogeneous geometries of the reactor core increases computational cost in terms of memory and time, whereas the multigroup CMFD reduces the computational cost. The reactor condition does not change at every time step, which is a vital point for the utilization of CMFD. CMFD correction factors are updated from the transport solution whenever the reactor core condition changes, and the simulation continues until the end. The transport solution is adjusted once CMFD achieves the solution. The flux-weighted method is used for rod decusping to update the partially inserted control rod cell material, which maintains the solution's stability. A smaller time-step size is needed to obtain an accurate solution, which increases the computational cost. The adaptive step-size control algorithm is robust for controlling the time step size. This algorithm is based on local errors and has the potential capability to accept or reject the solution. Several numerical problems are selected to analyze the performance and numerical accuracy of parallel computing, rod decusping, and adaptive time step control. Lastly, a typical pressurized LWR was chosen to study the rod-ejection accident.

• Journal of National Security and Military Science
• /
• s.1
• /
• pp.345-360
• /
• 2003

To build an information oriented armed forces, the Korean military telecommunication networks adopt TCP/IP standard communication infrastructures based on ATM packet switched networks. Utilizing this network infrastructure, the Korean armed forces also applies to the areas of battleship management for efficient operation command controls and resource management for efficient resource allocations. In this military communication networks, it is essential to determine the least cost network topology under equal performance and reliability constraints. Basically, this type of communication network design problem is known in the literature as an NP Hard problem. As the number of network node increases, it is very hard to obtain an optimal solution in polynomial time. Therefore, it is reasonable to use a heuristic algorithm which provides a good solution with minimal computational efforts. In this study, we developed a simulated annealing based heuristic algorithm which can be utilized for the design of military communication networks. The developed algorithm provides a good packet switched network topology which satisfies a given set of performance and reliability constraints with reasonable computation times.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.157-160
• /
• 2001

This paper has been studied a Adaptive Mutation rate Genetic Algorithm Processor. Genetic Algorithm(GA) has some control parameters such as the probability of bit mutation or the probability of crossover. These value give a priori by the designer There exists a wide variety of values for for control parameters and it is difficult to find the best choice of these values in order to optimize the behavior of a particular GA. We proposed a Adaptive mutation rate GA within a steady-state genetic algorithm in order to provide a self-adapting mutation mechanism. In this paper, the proposed a adaptive mutation rate GAP is implemented on the FPGA board with a APEX EP20K600EBC652-3 devices. The proposed a adaptive mutation rate GAP increased the speed of finding optimal solution by about 10%, and increased probability of finding the optimal solution more than the conventional GAP