http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : 하정훈 ( Chung Hun Ha ) (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
-
몬테카를로 DEA를 이용한 불확실성을 고려한 효율적 공급자 선정
하정훈(Chung hun Ha) 한국산업경영시스템학회 2015 한국산업경영시스템학회지 Vol.38 No.1
Selection of efficient supplier is a very important process as risk or uncertainty of a supply chain and its environment are increasing. Previous deterministic DEA and probabilistic DEAs are very limited to handle various types of risk and uncertainty. In this paper, I propose an improved probabilistic DEA which consists of two steps; Monte Carlo simulation and statistical decision making. The simulation results show that the proposed method is proper to distinguish supplier's performance and provide statistical decision background.
-
Agent-Based Model을 활용한 자동차 예비부품 장기수요예측
이상욱(Sang wook Lee),하정훈(Chung hun Ha) 한국산업경영시스템학회 2015 한국산업경영시스템학회지 Vol.38 No.1
Spare part management is very important to products that have large number of parts and long lifecycle such as automobile and aircraft. Supply chain must support immediate procurement for repair. However, it is not easy to handle spare parts efficiently due to huge stock keeping units. Qualified forecasting is the basis for the supply chain to achieve the goal. In this paper, we propose an agent based modeling approach that can deal with various factors simultaneously without mathematical modeling. Simulation results show that the proposed method is reasonable to describe demand generation process, and consequently, to forecast demand of spare parts in long-term perspective.
-
공구유연성과 공구관련제약을 고려한 통합공정일정계획을 위한 유전알고리즘
김영남(Young Nam Kim),하정훈(Chung hun Ha) 한국산업경영시스템학회 2017 한국산업경영시스템학회지 Vol.40 No.2
This paper proposes an improved standard genetic algorithm (GA) of making a near optimal schedule for integrated process planning and scheduling problem (IPPS) considering tool flexibility and tool related constraints. Process planning involves the selection of operations and the allocation of resources. Scheduling, meanwhile, determines the sequence order in which operations are executed on each machine. Due to the high degree of complexity, traditionally, a sequential approach has been preferred, which determines process planning firstly and then performs scheduling independently based on the results. The two sub-problems, however, are complicatedly interrelated to each other, so the IPPS tend to solve the two problems simultaneously. Although many studies for IPPS have been conducted in the past, tool flexibility and capacity constraints are rarely considered. Various meta-heuristics, especially GA, have been applied for IPPS, but the performance is yet satisfactory. To improve solution quality against computation time in GA, we adopted three methods. First, we used a random circular queue during generation of an initial population. It can provide sufficient diversity of individuals at the beginning of GA. Second, we adopted an inferior selection to choose the parents for the crossover and mutation operations. It helps to maintain exploitation capability throughout the evolution process. Third, we employed a modification of the hybrid scheduling algorithm to decode the chromosome of the individual into a schedule, which can generate an active and non-delay schedule. The experimental results show that our proposed algorithm is superior to the current best evolutionary algorithms at most benchmark problems.
-
장치산업의 라인별 평가를 위한 DEA-Super-Efficiency 모형에서의 정성적 평가자료의 활용
옥창수 ( Chang Soo Ok ),이영관 ( Young Kwan Lee ),하정훈 ( Chung Hun Ha ) (주)엘지씨엔에스(구 LGCNS 엔트루정보기술연구소) 2012 Entrue Journal of Information Technology Vol.11 No.2
본 연구는 화학 장치산업에서 생산라인 또는 의사결정단위를 평가하는 방안으로 개선된 DEA-Super-Efficiency 모델을 제안한다. 먼저, 화학산업 생산라인의 성과측정 또는 효율성을 평가하는데 고려되어야 하는 사항을 제시하고 이를 반영하기 위한 성과지표의 선정에 대하여 토의한다. 다품종 생산으로 인한 생산 효율 저하나 제조 난이도를 고려하기 위한 평가지표를 제안한다. 특히, 생산라인별 향후 수익 가능성이나 관련 산업의 시황에 따른 평가의 왜곡을 방지하기 위하여 경영층을 대상으로 설문조사를 실시하고 이 정성 데이터를 생산라인 평가에 활용한다. 이와 같이 생산라인의 공정한 평가를 위하여 정량적 데이터를 바탕으로한 여러 성과지표를 고려함과 동시에 각 생산라인의 가능성이나 예측 정보에 대한 정성 데이터를 활용하는 새로운 Super-Efficiency 모델을 제안하고 이에 대한 적용방법에 대하여 논의한다. This study proposes a new DEA-super-efficiency model utilizing qualitative data to evaluate production lines or DMUs (Decision Making Units) in chemical industry. We pointed out characteristics of chemical industry to be considered in evalua-tion of production lines. In consideration of these features a DEA-Super-Efficiency is devised to assess DMUs with several key performance indices(KPIs). The proposed model is capable of utilizing various KPIs simultaneously and discriminating efficient DMUs in the appraisal of production lines. In addition, it gives a way to utilize some qualitative information such as market impact and potential profit in assessment of DMUs. We demonstrate the effectiveness of our approach with a case study.
ScienceON
스콜라연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
