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.

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky

This research is to select a path planning algorithm to maximize survivability for Unmanned Aerial Vehicle(UAV). An UAV is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are currently employed in many military missions(surveillance, reconnaissance, communication relay, targeting, strike etc.) and a number of civilian applications(communication service, broadcast service, traffic control support, monitoring, measurement etc.). In this research, a mathematical programming model is suggested by using MRPP(Most Reliable Path Problem) and verified by using ILOG CPLEX. A path planning algorithm for UAV is selected by comparing of SPP(Shortest Path Problem) algorithms which transfer MRPP into SPP.

Reliability has been considered as a one of the major design measures in various industrial and military systems. The main objective is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for the problem that determin

The large-scale disasters occur to unexpected accidents such as natural disasters(earthquake, typhoon, tsunami, etc.), and human-caused accidents(fire, collapse, terror etc.). Rescue teams perform rescue activities to save many lives in large-scale disaster area. The main purpose of this study is to compose a optimal routing planning for rescue of multiple victims in disaster area. A realistic routing planning with rescue limit time which considers rehabilitation and reconstruction will be suggested in this study. A mathematical programming model and a hybrid genetic algorithm will be suggested to minimize the total spending time. By comparing the result, the suggested algorithm gives a better solution than existing algorithms.

일반적으로 현미를 발아시킬 경우 다양한 효소의 활성화로 인하여 GABA, ferulic acid, arabinoxylan, inositol 등의 기능성 성분들이 증가될 뿐만 아니라 조직을 연화시켜 현미의 식미를 개선시키는 것으로 알려져 있다. GABA는 발아현미에 존재하는 기능성 물질 중의 하나로 비단백질 아미노산이다. 본 연구의 목적은 발아 후 품종별 GABA 함량의 변화를 측정하고자 하였으며 이와 함께 vitamin E의 변화와 항산화력의 변화를 측정하고자 하였다. GABA 함량은 비색법을 이용하였고 vitamin E는 HPLC 방법을 항산화력은 ABTS와 DPPH 라디칼 소거능을 이용하여 측정하였다. 본 연구 결과 품종별 현미는 발아 과정을 통하여 GABA 함량은 약 10배 이상 그리고 vitamin E의 경우 tocotrienol이 상당히 증가하였으며 항산화 활성에는 전반적으로 변화가 없는 것으로 나타났다. 특히 큰눈 발아 현미의 경우 GABA 함량이 다른 품종에 비해 월등히 높았고 vitamin E 함량과 항산화 활성은 신명흑찰 발아현미가 높은 값을 나타내었다. 본 연구결과 현미를 발아시키면 GABA 및 vitamin E 등과 같은 생리활성 물질이 증가되고 항산화 활성이 그대로 유지된 기능성 쌀 가공품의 원료를 얻을 수 있을 것으로 생각한다.

  The main objective of this study is to find out the shortest path of the vehicle routing problem with time window constraints by using both genetic algorithm and heuristic. Hard time constraints were considered to the vehicle routing problem in this sug

본 연구는 기계고장 시 대체경로를 고려한 새로운 유사계수와 주어진 기간 내 수요변화를 고려하여 제조 셀을 구성하는 방법론을 개발하는 것이다. 본 연구의 방법론은 2단계로 나누어진다. 1단계에서는 기계고장 시 이용 가능한 대체경로를 고려하여 새로운 유사계수를 제시하고 유전자 알고리즘을 활용하여 부품 군을 식별하는 것이다. 셀 응용의 성패를 좌우하는 주요한 요소들 중 하나는 수요변화에 대한 유연성으로서 수요변화, 이용 가능한 기계의 능력 및 납기일에 따라