http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
유전자 알고리즘을 활용한 부품 군의 형성과 수요 변화하의 기계 셀 설계
전건욱(Geonwook Jeon) 한국산업경영시스템학회 2005 한국산업경영시스템학회지 Vol.28 No.3
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 셀을 재구성하기가 쉬운 일은 아닐 것이다. 대부분의 논문에서 제안한 방법들은 단일기간에 대한 고정 수요를 고려하였으나, 수요의 변화로 인하여 셀 설계는 대부분의 연구에서 고려한 단일기간보다는 장기적인 면을 고려해야 할 것이다. 수요가 변화하는 상황에서 운용요소와 일정요소를 고려한 셀 구성에 대한 새로운 방법론을 2단계에 소개한다.
전건욱(Geonwook Jeon),강성진(Sung-Jin Kang) 한국정책분석평가학회 2005 政策分析評價學會報 Vol.15 No.3
The Korean army is tends to mainly operate for preparation of military evaluation and accident prevention so far, when focused on unit management. Also it is being operated both training and unit management with restricted manpower, and it endeavors to improve the efficiency of unit management. The main objective of this study is to suggest a new methodology for relative efficiencies of the military units which is similar in size. The methodology used the IDEA(Imprecise Data Envelopment Analysis) model which is able to measure relative efficiencies for similar units and complement the drawbacks of the DEA(Data Envelopment Analysis). When the input and output variables are selected, efficient and inefficient military units were identified by using IDEA model. The IDEA model is able to analyze specific units where the inefficiency exists. This study also suggests both an additive IDEA model to become an efficient unit and profiling model to identify priority ranking between efficient units. The suggested models from this study are able to apply in all areas which requires efficiency scores between groups.
A*PS-PGA를 이용한 무인 항공기 생존성 극대화 경로 계획
김기태(Ki Tae Kim),전건욱(Geonwook Jeon) 한국산업경영시스템학회 2011 한국산업경영시스템학회지 Vol.34 No.3
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 or uninhabitable for human. UAVs are currently employed in many military missions such as reconnaissance, surveillance, enemy radar jamming, decoying, suppression of enemy air defense (SEAD), fixed and moving target attack, and air-to-air combat. UAVs also are employed in a number of civilian applications such as monitoring ozone depletion, inclement weather, traffic congestion, and taking images of dangerous territory. For accomplishing the UAV’s missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a A*PS-PGA (A-star with Post Smoothing-Parallel Genetic Algorithm) for an UAV’s path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and TSP (Traveling Salesman Problem). A path planning algorithm for UAV is applied by transforming MRPP into SPP (Shortest Path Problem).
하이브리드 병렬 유전자 알고리즘을 이용한 최적 신뢰도-중복 할당 문제
김기태(Ki Tae Kim),전건욱(Geonwook Jeon) 대한산업공학회 2010 산업공학 Vol.23 No.2
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.
김흥섭(Heung-seob, Kim),전건욱(Geonwook, Jeon) 대한산업공학회 2011 대한산업공학회 추계학술대회논문집 Vol.2011 No.11
Reliability is defined as a probability that a product/service will operate properly for a specified period of time under the design operating conditions without failure and it has been considered as one of the major design parameters in the field of industries. Reliability-Redundancy Optimization Problem(ROP) involves selection of components with multiple choices and redundancy levels for maximizing system reliability with constraints such as cost, weight, etc. However, in practice both active and cold standby redundancies may be used within a particular system design. Therefore, a redundancy strategy (active, cold standby) for each subsystem in order to maximize system reliability is considered in this study. Due to the nature of ROP, i.e. NP-hard problem, Parallel Particle Swarm Optimization(PPSO) technique is proposed to solve the mathmatical programming model and it gives consistently better quality solutions than existing studies for benchmark problem. This study is applied to the Multi-Spectral Camera(MSC) system of ARIRANG-2 Satellite as a actual system. The numerical experimental results of applied exercise are presented as instances of recommended design configurations.
김흥섭(Heung-Seob Kim),전건욱(Geonwook Jeon) 한국항공우주학회 2011 韓國航空宇宙學會誌 Vol.39 No.12
신뢰도란 임의 시스템이 주어진 운용환경 하에서 의도한 기간 동안 의도된 기능을 정상적으로 수행할 확률로 정의된다. 신뢰도-중복 최적화 문제(RROP)는 비용, 무게 등의 제약 내에서 시스템의 신뢰도를 최대화할 수 있는 최적의 부품을 선택하고, 부품수와 중복전략 (활성/대기중복)을 결정하는 문제이다. 본 연구에서는 아리랑위성 2호의 다채널광학카메라 (MSC) 시스템의 설계 구조를 바탕으로 RROP의 수리모형을 제시하고, NP-hard인 RROP의 해법으로써 병렬 개체군집최적화(PPSO) 알고리즘을 제안하였다. RROP 예제의 수치실험 결과는 계획된 수명기간에서 신뢰도를 최대화하는 시스템의 설계 구조를 제시한다. Reliability is defined as a probability that a system will operate properly for a specified period of time under the design operating conditions without failure. Reliability-Redundancy Optimization Problem(RROP) involves selection of components with multiple choices, redundancy levels and redundancy strategy(Active or Standby) for maximizing system reliability with constraints such as cost, weight, etc. Based on the design configuration of Multi-Spectral Camera(MSC) system of KOMPSAT-2, the mathematical programming model for RROP is suggested in this study. Due to the nature of RROP, i.e. NP-hard problem, Parallel Particle Swarm Optimization(PPSO) algorithm is proposed to solve it. The result of the numerical experiment for RROP is presented as instance of recommended design configuration at some mission time.