확률적 시뮬레이션 기반 AGV 배차

최이(Choe, Ri),박태진(Park, Tae-Jin),류광렬(Ryu, Kwang-Ryel) 한국항해항만학회 2008 한국항해항만학회지 Vol.32 No.10

자동화 컨테이너 터미널에서 안벽크레인, AGV (Automated Guided Vehicle)와 같은 하역장비의 작업은 수많은 요인에 영향을 받으며, 이로 인해 각 장비의 작업시간 예측에 있어 불확실성이 존재한다 이러한 불확실성은 AGV 배차를 어렵게 만들고 작업효율을 떨어뜨리는 주요 원인 중 하나이다. 본 논문에서는 이러한 불확실성에 대처하기 위하여 확률적 시뮬레이션 기반 AGV 배차 알고리즘을 제안한다. 제안 방안은 AGV에 작업을 할당할 때, 할당된 작업의 수행 및 이후 일정 기간 동안의 AGV의 작업에 대해 확률적 시뮬레이션을 여러 번 반복 수행하여 작업할당에 대한 평가치의 확률적 표본을 수집한다. 수집한 표본으로부터 평가의 기대치를 추정하고 이를 이용하여 대안을 평가함으로써 불확실성의 영향을 줄인다. 평가의 신뢰도를 높이기 위해서는 많은 수의 표본을 수집해야 하므로 실시간 제약 하에서 수집 가능한 확률적 표본의 수를 늘리기 위해 이벤트 기반의 고속 시뮬레이션을 디자인하였다. 시뮬레이션 실험을 통해 검증한 결과 불확실성이 있는 환경에서 제안방안의 성능이 정적인 환경을 가정하는 방안보다 뛰어남을 확인하였다. In an automated container terminal, various factors affect the operation of container handling equipment such as quay cranes and AGVs, and thus calculating the exact operation time is nearly infeasible. This uncertainty makes it difficult to dispatch AGVs well. In this paper, we propose a simulation-based AGV dispatching algorithm When dispatching an AGV to an operation, the proposed algorithm conducts multiple stochastic simulation for the succeeding AGV operations for the predetermined period to collect stochastic samples of the result of the dispatching. In the stochastic simulation, the uncertainty of crane operations is represented as a simple probability distribution and the operation time of a crane is determined according to this. A dispatching option is evaluated by the total delay time of quay cranes which is estimated by averaging the quay crane delay of each simulation In order to collect a sufficient number of samples that guarantee the credibility of the evaluation, we devised a high-speed simulator that simulates AGV operation The effectiveness of the proposed algorithm is validated by simulation experiments.

시뮬레이션을 기반(基盤)으로 하는 영업리윤율(營業利潤率) 추정(推定) 시스템

이창용 ( Chang-yong Yi ),김률희 ( Ryul-hee Kim ),임태경 ( Tea-kyung Lim ),김화중 ( Wha-jung Kim ),이동은 ( Dong-eun Lee ) 한국건축시공학회 2007 한국건축시공학회 학술발표대회 논문집 Vol.7 No.2

This paper introduces a system, Simulation based Stochastic Markup Estimation System (S2ME), for estimating optimum markup for a project. The system was designed and implemented to better represent the real world system involved in construction bidding. The findings obtained from the analysis of existing assumptions used in the previous quantitative markup estimation were incorporated to improve the accuracy and predictability of the S2ME. The existing methods has four categories of assumption as follows; (1) The number of competitors and who is the competitors are known, (2) A typical competitor, who is fictitious, is assumed for easy computation, (3) the ratio of bid price against cost estimate (B/C) is assumed to follow normal distribution, (4) The deterministic output obtained from the probabilistic equation of existing models is assumed to be acceptable. However, these assumptions compromise the accuracy of prediction. In practice, the bidding patterns of the bidders are randomized in competitive bidding. To complement the lack of accuracy contributed by these assumptions, budding project was randomly selected from the pool of bidding database in the simulation experiment. The probability to win the bid in the competitive bidding was computed using the profile of the competitors appeared in the selected bidding project record. The expected profit and probability to win the bid was calculated by selecting a bidding record randomly in an iteration of the simulation experiment under the assumption that the bidding pattern retained in historical bidding DB manifest revival. The existing computation, which is handled by means of deterministic procedure, were converted into stochastic model using simulation modeling and analysis technique as follows; (1) estimating the probability distribution functions of competitors`` B/C which were obtained from historical bidding DB, (2) analyzing the sensitivity against the increment of markup using normal distribution and actual probability distribution estimated by distribution fitting, (3) estimating the maximum expected profit and optimum markup range. In the case study, the best fitted probability distribution function was estimated using the historical bidding DB retaining the competitors`` bidding behavior so that the reliability was improved by estimating the output from simulation experiment.

Analytical and experimental exploration of sobol sequence based DoE for response estimation through hybrid simulation and polynomial chaos expansion

Rui Zhang,Chengyu Yang,Hetao Hou,Karlel Cornejo,Cheng Chen 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.2

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Metamodeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear singledegree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

고차의 추계장 함수와 이를 이용한 비통계학적 추계론적 유한요소해석

노혁천(Noh Hyuk-Chun) 대한토목학회 2006 대한토목학회논문집 A Vol.26 No.2A

본 연구에서는 급수전개를 이용한 추계론적 유한요소해석법의 개선을 위한 등 가몬테카를로 추계장함수를 제안하고 1차 Taylor전개를 이용한 추계론적 유한요소해석법인 가중적분법에 적용하였다. 일반적으로 1차 Taylor전개를 이용하는 수치해석법에서의 응답변화도는 고려하고 있는 추계장의 분산계수에 대하여 선형거동을 보인다. 그러나 몬테카를로 해석의 경우 추계장 분산계수에 대하여 비선형거동을 나타낸다. 이는 급수전개법의 1차 Taylor전개에 따른 선형특성에 기인한다. 따라서, 가중적분법에서 사용되는 Taylor전개된 변위벡터와 몬테카를로 해석에서의 변위벡터를 비교하고 이들 두 변위벡터 사이에 상호 불일치 하는 점을 고찰하여 몬테카를로 해석에서의 변위벡터와 등가의 변위벡터를 구성하고 이를 가중적분법에 적용하였다. 제안한 등가몬테카를로 추계장은 본래의 추계장 함수에 대한 고차함수로 주어진다. 평면구조에 대한 수치해석을 통하여 제안한 등기몬테카를로 추계장을 이용한 정식화의 타당성을 고찰하였다. 새로운 정식화는 기존의 1차 가중적분법을 위한 정식화 과정과 유사하게 수행할 수 있었다. In this paper, a stochastic field that is compatible with Monte Carlo simulation is suggested for an expansion-based stochastic analysis scheme of weighted integral method. Through investigation on the way of affection of stochastic field function on the displacement vector in the series expansion scheme, it is noticed that the stochastic field adopted in the weighted integral method is not compatible with that appears in the Monte Carlo simulation. As generally recognized in the field of stochastic mechanics, the response variability is not a linear function of the coefficient of variation of stochastic field but a nonlinear function with increasing variability as the intensity of uncertainty is increased. Employing the stochastic field suggested in this study, the response variability evaluated by means of the weighted integral scheme is reproduced with high precision even for uncertain fields with moderately large coefficient of variation. Besides, despite the fact that only the first-order expansion is employed, an outstanding agreement between the results of expansion-based weighted integral method and Monte Carlo simulation is achieved.

실무 활용성이 강화된 진보형 시뮬레이션 일정시스템

김률희(Kim Ryul-Hee),배태현(Bae Tae-Hyun),이동은(Lee Dong-Eun) 대한건축학회 2009 大韓建築學會論文集 : 構造系 Vol.25 No.5

This paper introduces an automated tool named Advanced Stochastic Simulation-based Scheduling system(AS3). The system automatically integrates CPM schedule data exported from P3 into it and computes the best fit Probability Distribution Functions (PDFs) of historical activity duration data. In addition, it defines activity durations using the PDFs identified, simulate the schedule network, and estimates the best fit PDF of project completion times (PCTs). AS3 integrates the automated best fitting function which identifies the exact distribution of PCTs using the “goodness of fit” principles into existing simulation-based scheduling method. It improves the reliability of simulation-based scheduling by effectively dealing the uncertainties of the activity durations rather than existing systems dose. Furthermore, it increases the usability of the schedule data obtained from commercial CPM softwares, and effectively handle the variability of the PCTs by finding the best fit PDF of PCTs. It is implemented as an easy-to-use computerized tool programmed in MATLAB. AS3 can make significant contribute to the field of simulation-based scheduling, because (1) it analyzes the effect of different distributions of activity durations on the distribution of the PCTs, (2) the reliability obtained by the system is higher than conventional simulation-based scheduling systems, (3) simplifies the tedious and burdensome process involved in finding the PDFs of the many activity durations, and (4) it is a welcome replacement for the normality assumptions used by most simulation-based scheduling researchers, and therefore increase the usability of simulation-based scheduling and generates more accurate results.

형상 파라미터 공차 변화에 따른 2선 대칭/비대칭 전송선로 크로스토크의 확률적 예측에 대한 연구

이재영(Jaeyoung Lee),이호상(Hosang Lee),나완수(Wansoo Nah) 한국전자파학회 2020 한국전자파학회논문지 Vol.31 No.11

본 논문에서는 형상 파라미터의 제작 공차 변화에 의한 2선 대칭/비대칭 전송선로의 크로스토크 전압을 예측하고자 확률적 예측 기법인 Generalized Polynomial Chaos Method (gPC)를 도입하고, 기존의 확률 예측 기법인 몬테카를로 시뮬레이션 (Monte-Calro simulation)을 이용한 예측을 병행하여 최종적으로 실제 측정된 크로스토크 전압과 비교하였다. 전송선로는 한 쌍의 마이크로스트립 신호선 형태로, 일반적인 대칭선로 구조와 크로스토크 저감 성능을 갖는 비대칭선로 구조를 기준으로 삼았다. 전송선로 구조 내에서 확률 변수 5가지를 정의하였고, 해당 변수들을 매개로 몬테카를로 시뮬레이션과 gPC 방법을 병행하여 진행하였으며, 확률적 예측 결과를 토대로 대칭구조 및 비대칭구조 전송선로에서의 크로스토크 전압 변화를 도출하였으며, 제작 공차에 대하여 어떤 구조가 더 민감한지를 파악하였다. 최종적으로 실제 측정된 크로스토크 전압과 비교하여 확률적 예측 기법의 정합성을 파악하였고, 비대칭 전송선로에서의 크로스토크 저감 성능이 형상 파라미터의 제작 공차에 의하여 크게 훼손되지 않음을 확인하였다. In this study, a generalized polynomial chaos method (gPC), which is a stochastic estimation technique, was used to predict the crosstalk voltage of a two-conductor symmetric/asymmetric transmission line owing to changes in the manufacturing tolerance of the geometrical parameters. In addition, a Monte-Carlo simulation, a conventional estimation method, was conducted in parallel with the gPC, and the results were compared with the actual measured crosstalk. A pair of microstrip signal lines were applied with symmetric and asymmetric structures, achieving a reduction in the crosstalk. A total of five geometrical parameters were defined as random variables, and a stochastic simulation was conducted in parallel for comparison with the crosstalk results of the gPC and Monte-Carlo simulations. Based on the stochastic estimation, we derived the change in crosstalk on the transmission lines and identified which structures are more sensitive to tolerance. Finally, the effectiveness of the stochastic estimation was determined by comparing the actual data, and it was confirmed that the performance in reducing the crosstalk under an asymmetric structure was not significantly hindered based on the manufacturing tolerance of the geometrical parameters.

시뮬레이션을 基盤으로 하는 투찰율 推定(대한주택공사 전자입찰 공시자료를 사용한 사례연구)

임태경,김률희,이창용,이동은 대한건축학회지회연합회 2007 대한건축학회지회연합회 학술발표대회논문집 Vol.2007 No.1

This paper introduces a system called Simulation-based Stochastic Bidding Cost Estimation System (S2BC) that use simulation modeling and analysis technique. It better represents the real world system involved in construction bidding. The prediction accuracy was compromised because of the assumptions which existing models have adopted. However, The S2BC complements the lack of accuracy. Historical bidding data obtained from the Korea National Housing Corporation was used to validate the method. Bidding projects in the Historical DB were selected by random sampling. The ration of bidding let was calculated using the occurrence of participants who entered into a specific bidding. On the assumption that bidding pattern retained on the historical DB has reproducibility, the probability of winning was computed using the cumulative probability distribution that is obtained from the user defined numbe r of random sampling of bidding projects out of the Historical DB. The existing computation, which is handled by means of deterministic procedure, was converted into stochastic model using simulation modeling and analysis technique. The best fitted probability distribution function is estimated using the historical data. The reliability of estimating probability of winning on specified bidding let is improved using the S2BC.

Stochastic finite element analysis of plate structures by weighted integral method

Choi, Chang-Koon,Noh, Hyuk-Chun Techno-Press 1996 Structural Engineering and Mechanics, An Int'l Jou Vol.4 No.6

In stochastic analysis, the randomness of the structural parameters is taken into consideration and the response variability is obtained in addition to the conventional (mean) response. In the present paper the structural response variability of plate structure is calculated using the weighted integral method and is compared with the results obtained by different methods. The stochastic field is assumed to be normally distributed and to have the homogeneity. The decomposition of strain-displacement matrix enabled us to extend the formulation to the stochastic analysis with the quadratic elements in the weighted integral method. A new auto-correlation function is derived considering the uncertainty of plate thickness. The results obtained in the numerical examples by two different methods, i.e., weighted integral method and Monte Carlo simulation, are in a close agreement. In the case of the variable plate thickness, the obtained results are in good agreement with those of Lawrence and Monte Carlo simulation.

A Study on the Discrete Event System Simulation Application in Inventory System

Xiang-wen Li,Hong-mei Xu,Xin-ying Wang 한국멀티미디어학회 2006 한국멀티미디어학회 국제학술대회 Vol.2006 No.-

One of the typical discrete event systems is the inventory system. The paper establishes the mathematical model of the stochastic inventory system, and then the simulation strategy is put forward by means of the discrete event system simulation technology and the simulation model is established. Therefore, the best inventory strategy is applied with the method of system simulation.

네스팅 기법을 활용한 공정 및 일정 통합 시뮬레이션 시스템

이창용(Yi Chang-Yong),이동은(Lee Dong-Eun) 대한건축학회 2009 大韓建築學會論文集 : 構造系 Vol.25 No.9

Simulation applications for analyzing the productivity of construction operations at operation level and project schedules at project level are crucial methods in project management. The application at two different levels should be very tightly linked to each other in practice. However, appropriate integration at the levels is not achieved in that existing systems do not support to integrate operation models into a schedule model. This paper presents a new approach named to Discrete Event Simulation-Nesting modeling approach, which supports not only productivity analysis at operation level but also schedule management at a project level. The system developed by the authors allows creating operation models at the operation level, maintaining them in operation model library, executing sensitivity analysis to find the behaviors of the operation models when different combination of resources are used as existing DES systems do. On top of the conventional functions, the new system facilitates to find the optimum solution of resource combinations which satisfy the user’s interest by computing the hourly productivity and the hourly cost of the operation. The operation models are integrated into an activity of the schedule model. When a complete schedule model is established by nesting operation models into the schedule model, stochastic simulation based scheduling is executed. A case study is presented to demonstrate the new simulation system and verify the validity of the system.