• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.15-26
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• 2014

This paper proposes a Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients (MPSO-TVAC) for solving economic load dispatch (ELD) problem. Due to prohibited operating zones (POZ) and ramp rate limits of the practical generators, the ELD problems become nonlinear and nonconvex optimization problem. Furthermore, the ELD problem may be more complicated if transmission losses are considered. Particle swarm optimization (PSO) is one of the famous heuristic methods for solving nonconvex problems. However, this method may suffer to trap at local minima especially for multimodal problem. To improve the solution quality and robustness of PSO algorithm, a new best neighbour particle called 'rbest' is proposed. The rbest provides extra information for each particle that is randomly selected from other best particles in order to diversify the movement of particle and avoid premature convergence. The effectiveness of MPSO-TVAC algorithm is tested on different power systems with POZ, ramp-rate limits and transmission loss constraints. To validate the performances of the proposed algorithm, comparative studies have been carried out in terms of convergence characteristic, solution quality, computation time and robustness. Simulation results found that the proposed MPSO-TVAC algorithm has good solution quality and more robust than other methods reported in previous work.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.490-498
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• 2013

This paper discusses the application of evolutionary multi-objective optimization algorithms namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Modified NSGA-II (MNSGA-II) for solving the Combined Economic Emission Dispatch (CEED) problem with valve-point loading. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a non-smooth optimization problem. IEEE 57-bus and IEEE 118-bus systems are taken to validate its effectiveness of NSGA-II and MNSGA-II. To compare the Pareto-front obtained using NSGA-II and MNSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Furthermore, three different performance metrics such as convergence, diversity and Inverted Generational Distance (IGD) are calculated for evaluating the closeness of obtained Pareto-fronts. Numerical results reveal that MNSGA-II algorithm performs better than NSGA-II algorithm to solve the CEED problem effectively.

• Journal of the military operations research society of Korea
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• v.9 no.1
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• pp.29-49
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• 1983

The algorithm developed in this paper utilized kettelle's [1] idea of the undominated allocation sequence and his way of tableau computation to solve the more general spares allocation problem in the system availability optimization. The algorithm is to optimally allocate resources to the independent modules which are connected to be series/parallel/mixed system configurations. It has advantages over the standard dynamic programming algorithm by eliminating the need for backtracking and by solving the allocation problem for any budget size. By careful heuristic inspection the algorithm can be made very efficient for manual calculations because large blocks of cells can be eliminated from computation. A numerical example is provided to illustrate the allocation algorithm.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.222-224
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• 2006

This paper addresses a particle swarm optimization-based approach for solving a generating unit maintenance scheduling problem(GMS) with some constraints. We focus on the power system reliability such as reserve ratio better than cost function as the objective function of GMS problem. It is shown that particle swarm optimization-based method is effective in obtaining feasible schedules such as GMS problem related to power system planning and operation. In this paper, we find the optimal solution of the GMS problem within a specific time horizon using particle swarm optimization algorithm. Simple case study with 16-generators system is applicable to the GMS problem. From the result, we can conclude that PSO is enough to look for the optimal solution properly in the generating unit maintenance scheduling problem.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.27-34
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• 2013

This paper deals with the performance anlysis of CCA adaptive equalization algorithm, that is used for reduction of intersymbol interference at the receiving side which occurs in the time dispersive communication channel. Basically, this algorithm is borned for the solving phase unrecovery problem in the CMA equalizer, and the comines the concept of DDA (Decision Directed Algorithm) and RCA (Reduce Constellation Algorithm). The DDA has a stable convergence characteristics in unilevel signal, but not in the number of levels in multilevel signal such as QAM, so it has unstable problem. The RCA does not provide reliable initial convergence. And even after convergence, the equalization noise due to the steady state misadjustment exhibited by it is very high as compared to DDA. For the solving the abovemensioned point, the CCA adaptive eualization alogorithm has borned. In order to performance analysis of CCA algorithm, the recovered signal constellation that is the output of the equalizer, the convergence characteristic by the residual isi and MD (maximum distortion), the SER characteristic are used by computer simulation and it was compared with the DDA, RCA respectively. As a result of simulation, the DDA has superior performance than other algoithm, but it has a convergence unguarantee and unstability in the multilevel signal. In order to solving this problem, the CCA has more good performance than RCA in every performance index.

• Journal of the Korean School Mathematics Society
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• v.25 no.2
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• pp.105-124
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• 2022

The contents of fraction division in textbooks are important because there were changes in situations and problem solving methods in textbooks according to the revision of the curriculum and the contents of textbooks affect students' learning directly. So, this study analyzed the achievement standards of the curriculum and formula types and situations, and the introduction process of non-standard and standard algorithms presented in Korean mathematics textbooks. The results are follows: there was little difference in the achievement standards of the curriculum, but there was a difference in the arrangement of contents by grades in textbooks. There was a difference in the types of formula according to textbooks. And the situation became more diverse; recent textbooks have changed to the direction of using the non-standard and the standard algorithm in parallel. In conclusion, I proposed categorizing rather than splitting the types of fraction division, the connection of non-standard and standard algorithm, and the need to prepare methods to pursue generalization and justification according to the common characteristics in the process of introducing standard algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1708-1734
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• 2022

In the development of logistics system, the breakthrough of important technologies such as technology platform for logistics information management and control is the key content of the study. Based on Javascript and JQuery, the logistics system realizes real-time monitoring, collection of historical status data, statistical analysis and display, intelligent recommendation and other functions. In order to strengthen the cooperation of warehouse storage, enhance the utilization rate of resources, and achieve the purpose of real-time and visual supervision of transportation equipment and cargo tracking, this paper studies the VNF dynamic deployment and SFC routing problem in the network load change scenario based on the logistics system. The BIP model is used to model the VNF dynamic deployment and routing problem. The optimization objective is to minimize the total cost overhead generated by each SFCR. Furthermore, the application of the SFC mapping algorithm in the routing topology solving problem is proposed. Based on the concept of relative cost and the idea of topology transformation, the SFC-map algorithm can efficiently complete the dynamic deployment of VNF and the routing calculation of SFC by using multi-layer graph. In the simulation platform based on the logistics system, the proposed algorithm is compared with VNF-DRA algorithm and Provision Traffic algorithm in the network receiving rate, throughput, path end-to-end delay, deployment number, running time and utilization rate. According to the test results, it is verified that the test results of the optimization algorithm in this paper are obviously improved compared with the comparison method, and it has higher practical application and promotion value.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2422-2443
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• 2020

This paper studies a single-user Mobile Edge Computing (MEC) system where mobile device (MD) includes an application consisting of multiple computation components or tasks with dependencies. MD can offload part of each computation-intensive latency-sensitive task to the AP integrated with MEC server. In order to accomplish the application faultlessly, we calculate out the optimal task offloading strategy in a time-division manner for a predetermined execution order under the constraints of limited computation and communication resources. The problem is formulated as an optimization problem that can minimize the energy consumption of mobile device while satisfying the constraints of computation tasks and mobile device resources. The optimization problem is equivalently transformed into solving a nonlinear equation with a linear inequality constraint by leveraging the Lagrange Multiplier method. And the proposed dual Bi-Section Search algorithm Bi-JOTD can efficiently solve the nonlinear equation. In the outer Bi-Section Search, the proposed algorithm searches for the optimal Lagrangian multiplier variable between the lower and upper boundaries. The inner Bi-Section Search achieves the Lagrangian multiplier vector corresponding to a given variable receiving from the outer layer. Numerical results demonstrate that the proposed algorithm has significant performance improvement than other baselines. The novel scheme not only reduces the difficulty of problem solving, but also obtains less energy consumption and better performance.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.213-219
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• 2016

This paper presents a branch-and-bound algorithm for solving the concave minimization problem with upper bounded variables whose single constraint is linear. The algorithm uses simplex as partition element. Because the convex envelope which most tightly underestimates the concave function on the simplex is uniquely determined by solving the related linear equations. Every branching process generates two subsimplices one lower dimensional than the candidate simplex by adding 0 and upper bound constraints. Subsequently the feasible points are partitioned into two sets. During the bounding process, the linear programming problems defined over subsimplices are minimized to calculate the lower bound and to update the incumbent. Consequently the simplices which do certainly not contain the global minimum are excluded from consideration. The major advantage of the algorithm is that the subproblems are defined on the one less dimensinal space. It means that the amount of work required for the subproblem decreases whenever the branching occurs. Our approach can be applied to solving the concave minimization problems under knapsack type constraints.

• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.235-241
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• 2010

This paper has been studied about algorithm teaching methods for improving the problem-solving skills and creativity in rapidly changing information society. Especially the algorithms for teaching about computer is very important. Because it is effective learning content for finding the best solution to solve a problem and improve the students' logical thinking. However, teaching algorithms can be monotonous to children on account of using only computer and languages. So It needs to consider about the cognitive structure and level of elementary school students. Therefore, this study has the purpose to acquaint students with the principle of algorithm and improve problem-solving and creativity using games, not computer.