• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.65-73
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• 2017

The fifth generation(5G) of wireless networks will connect not only smart phone but also unimaginable things. Therefore, 5G cellular network is facing the soaring traffic demand of numerous user devices. To solve this problem, a huge amount of 5G base stations will need to be installed. The base station positioning problem is an NP-hard problem that does not know how long it will take to solve the problem. Because, it can not find an answer other than to check the number of all cases. In this paper, to solve the NP hard problem, we compare the tabu search and the genetic algorithm using real maps for optimal cell planning. We also perform Monte Carlo simulations to study the performance of the Tabu search and Genetic algorithm for 5G cell planning. As a results, Tabu search required 2.95 times less computation time than Genetic algorithm and showed accuracy difference of 2dBm.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.327-329
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• 2001

This paper presents the application of Parallel genetic algorithm and parallel tabu search to search an optimal solution of a unit commitment problem. The proposed method previously searches the solution globally using the parallel genetic algorithm, and then searches the solution locally using tabu search which has the good local search characteristic to reduce the computation time. This method combines the benefit of both method, and thus improves the performance. To show the usefulness of the proposed method, we simulated for 10 units system. Numerical results show the improvements of cost and computation time compared to previous obtained results.

• Proceedings of the KIEE Conference
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• summer
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• pp.36-38
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• 2004

This paper presents an application of parallel hybrid Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a recokiguration in distribution system. In parallel hybrid CA-TS, after CA operations, stings which are not emerged in the past population are selected in the reproduction procedure. After reproduction operation, if there are many strings which are in the past population, we add new random strings into the population, if there's no improvement for the predetermined iteration, local search procedure is executed by TS for the strings with high fitness function value. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution system in the reference paper.

• Proceedings of the KIEE Conference
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• summer
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• pp.446-448
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• 2004

This paper presents an application of parallel hybrid Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution system. In parallel hybrid GA-TS, after GA operations, strings which are not emerged in the past population are selected in the reproduction procedure. After reproduction operation, if there are many strings which are in the past population, we add new random strings into the population. If there's no improvement for the predetermined iteration, local search procedure is executed by f for the strings with high fitness function value. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a practical distribution system in Korea.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.8
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• pp.375-387
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• 2005

This paper presents an application of parallel Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution systems. The main objective of service restoration of distribution systems is, when a fault or overload occurs, to restore as much load as possible by transferring the do-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints, which is a combinatorial optimization problem. This problem has many constraints with many local minima to solve the optimal switch position. This paper develops parallel GA-TS algorithm for service restoration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solutions of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper $10\%$ of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC cluster system consists of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through ethernet switch based fast ethernet. To show the validity of the proposed method, proposed algorithm has been tested with a practical distribution system in Korea. From the simulation results, we can find that the proposed algorithm is efficient for the distribution system service restoration in terms of the solution quality, speedup, efficiency and computation time.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.556-564
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• 2004

This paper presents an application of parallel Genetic Algorithm-Tabu Search(GA-TS) algorithm to search an optimal solution of a reconfiguration in distribution system. The aim of the reconfiguration of distribution systems is to determine switch position to be opened for loss minimization in the radial distribution systems, which is a discrete optimization problem. This problem has many constraints and very difficult to solve the optimal switch position because it has many local minima. This paper develops parallel GA-TS algorithm for reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10% of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node aster predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium Ⅳ CPU and is connected with others through ethernet switch based fast ethernet. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution systems in the reference paper. From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution qualify. speedup. efficiency and computation time.