• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.4
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• pp.566-578
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• 2017

For optimizing the operation plan when strike packages attack multiple targets, this article suggests a new mathematical model and a parallel hybrid genetic algorithm (PHGA) as a solution methodology. In the model, a package can assault multiple targets on a sortie and permitted the use of mixed munitions for a target. Furthermore, because the survival probability of a package depends on a flight route, it is formulated as a mixed integer programming which is synthesized the models for vehicle routing and weapon-target assignment. The hybrid strategy of the solution method (PHGA) is also implemented by the separation of functions of a GA and an exact solution method using ILOG CPLEX. The GA searches the flight routes of packages, and CPLEX assigns the munitions of a package to the targets on its way. The parallelism enhances the likelihood seeking the optimal solution via the collaboration among the HGAs.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.48-55
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• 2008

In this paper, we propose a hybrid fuzzy controller for high performance. Hybrid fuzzy controller are combined Fuzzy and PID controller. In tuning the controller, the parameters of PID and the factors fuzzy controllers were obtained from the model identification and by using genetic algorithms, respectively. Simulation examples demonstrated a better performance of the proposed controller than conventional ones.

• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.107-114
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• 2011

Traveling salesman problem is to minimize the total cost for a traveling salesman who wants to make a tour given finite number of cities along with the cost of travel between each pair them, visiting each cities exactly once before returning home. Traveling salesman problem is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study suggests a hybrid parallel genetic algorithm(HPGA) for traveling salesman problem The suggested algorithm combines parallel genetic algorithm, nearest neighbor search, and 2-opt. The suggested algorithm has been tested on 7 problems in TSPLIB and compared the results of existing methods(heuristics, meta-heuristics, hybrid, and parallel). Experimental results shows that HPGA could obtain good solution in total travel distance minimization.

• IE interfaces
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• v.23 no.2
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• pp.147-155
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• 2010

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.