Operations Research, Systems Engineering and Industrial Engineering Commons^™

Floor Evacuation Simulation Based On Bim And Mr, Zhijie Li, Shuangyu Ma, Changhua Li, Xiao Liang, Jie Zhang

Journal of System Simulation

Abstract: Facing with the problem that the floor evacuation simulation only annotates the floor plan route, which is relatively single and not intuitive, a 3D building evacuation simulation method integrating mixed reality and building information model is proposed. The BIM components are reasonably planned and segmented, and reasonable annotation is performed. The BIM information is routed through the surface area heuristic optimization algorithm based on the bounding volume hierarchy. The evacuation simulation process is imported into the Microsoft Hololens2 hardware platform using the Unity3D development engine. The experimental results show that, compared with the previous evacuation simulation expressed only …

Multiagent Following Multileader Algorithm Based On K-Means Clustering, Guodong Yuan, Ming He, Ziyu Ma, Weishi Zhang, Xueda Liu, Wei Li

Journal of System Simulation

Abstract: Three K-means clustering algorithms are proposed to prevent chaos in the formation of a multi-agent system (MAS) with multiple leaders. The algorithm divides the cluster into communities with the same number of leaders, and the agents within the community will follow the same leader. Among the three proposed algorithms, algorithm #1 is suitable for scenarios with widely distributed agents wherein rapid consensus can be achieved in the shortest time; algorithm #2 is suitable for scenarios with a sparse agent distribution and effectively prevented agent collisions; and algorithm #3 exhibits rapid convergence and considerably reduces the MAS control cost, …

Simulation On Cooperative Control Of Connected And Automated Vehicles At Interchange Based On Petri Net, Mingbao Pang, Zhen Liu

Journal of System Simulation

Abstract: To improve the traffic efficiency of interchange, a simulation model of complete process is built by timed Petri net (TdPN) considering multiple separation and merging behaviors in the process of connected and automated vehicles (CAVs) passing through the interchange. In the light of vehicle priority, a speed guidance strategy is proposed and a CAVs cooperative control model is established, so as to form a complete interchange TdPN model. This method is verified by simulation and compared with the cooperative control method of interchange exit and its connecting area, cooperative control method of multi-merging areas within the interchange. The results …

Multi-Strategy Hybrid Abc For Microarray High-Dimensional Feature Selection, Chuandong Qin, Baosheng Li, Baole Han

Journal of System Simulation

Abstract: Traditional feature selection approaches have major limitations for high-dimensional microarrays, and it is difficult to accurately and efficiently propose the best feature subset. To address this problem, a multi-strategy hybrid artificial bee colony (ABC) algorithm based on wrapper is proposed, which mixes chaotic opposition-based learning strategy, elite guidance strategy, and Mantegna Lévy distribution strategy, and proposes two new search strategies in the employed and onlooker bee phases respectively. A new objective function is proposed for the microarray high-dimensional feature selection problem, which balances the optimal performance of the model with the minimization of the feature subset …

Multi-Media Energy Planning Optimization Of Steel Based On Improved Moea/D, Hongcai Ouyang, Dinghui Wu, Junyan Fan, Jing Wang

Journal of System Simulation

Abstract: To address the problems of multi-media iron and steel energy planning model with more variables, complex constraints and high difficulty in model solving, an improved MOEA/D (decomposition-based multi-objective evolutionary algorithm) based on adaptive neighborhood is proposed to realize multi-media energy planning optimization. Considering the characteristics of TOU price and the buffer effect of gas holder, the objective function to minimize operation cost and total energy consumption is constructed. And the model constraints are designed such as energy supply and demand balance. The decoding method based on energy production and consumption rules is designed to determine the target value. The …

Costume Pattern Sketch Colorization And Style Transfer Based On Neural Network, Xingquan Cai, Zhijun Li, Mengyao Xi, Haiyan Sun

Journal of System Simulation

Abstract: Aiming at the problems of color overflow in pattern sketch colorization and lack of fabric texture features in style transfer, this paper proposes a method of costume pattern sketch colorization and style transfer based on neural network. This paper initializes the data set, collects the costume pattern image, extracts the costume pattern sketch, synthesizes the costume pattern sketch with color features and constructs the style data set. The research builds the conditional generative adversarial nets and achieves the costume pattern sketch with color features colorization based on the generator. The study constructs a convolutional neural network model, uses the …

Dynamic Performance Evaluation Method For Transfer In Rail Transit Station Based On Station Simulation And Lstm, Bisheng He, Hongxiang Zhang, Yongjun Zhu, Gongyuan Lu

Journal of System Simulation

Abstract: Given the boom increasing of rail transit passenger volume, the dynamic performance evaluation method for transfer in rail transit stations based on machine learning are proposed to effectively evaluate the performance of the transfer station in different scenarios. Based on the proposed dynamic performance evaluation indexes of effective transfer number, transfer time and congestion, the influence factors of station dynamic performance are analyzed. The simulation model integrated train operation and pedestrian movement is built to provide the time-series data for the machine learning method. The long short-term memory (LSTM) is implemented to forecast the evaluation indicators, and the …

Application Of Digital Twin Model In Grinding Of Bearing Rings, Hongbin Liu, Zhiqiang Shen, Yize Wang, Ming Qiu, Wenrong Lin

Journal of System Simulation

Abstract: The digital twin model can effectively promote the virtual-real interaction between the actual product and the product model. Aiming at the grinding force generated in the grinding process of spherical roller bearings, this paper constructs the bearing ring raceway grinding process by performing dynamics, contact algorithm modeling and rigid-flexible coupling treatment on the components of the grinding work area. The digital twin model completes the virtual mapping of the grinding work area of the bearing ring in the digital space. The model is used to analyze and test the process parameters such as the grinding wheel linear speed and …

Integrated Soft Sensor Modeling Of Fermentation Process Based On Transfer Component Analysis, Yuesheng Zhou, Weili Xiong

Journal of System Simulation

Abstract: The Penicillin fermentation process is an uncertain and multi-stage process. There are different working conditions among different batch fermentation processes, and the distribution of process data is not necessarily the same, which degrades the performance of the traditional soft sensing model. Combined with the transfer learning strategy and Gaussian mixture model, a multi-model ensemble soft sensor modeling method based on transfer component analysis is proposed. In this method, the transfer component analysis is used to get the shared feature mapping matrix between samples, and adapt the edge probability distribution of labeled dataset and unlabeled dataset; the modeling data are …

Hyper-Heuristic Three Dimensional Eda For Solving Green Two-Sided Assembly Line Balancing Problem, Rong Hu, Shuai Ding, Bin Qian, Changsheng Zhang

Journal of System Simulation

Abstract: This paper establishes a model for green robotic two-sided assembly line balancing problem of type-I, and a hyper-heuristic three dimensional estimation of distribution algorithm (HH3DEDA) is proposed for solving this problem. In HH3DEDA, a combinatorial encoding rule based on process selectors is designed via considering the characteristics of the problem. Then, HH3DEDA with a high and low layered structure is proposed. In the upper layer, the three-dimensional probability matrix is utilized to learn high-quality high individual block structure and its distribution information, and then the matrix is sampled to generate new high level individuals. Each high individual is …

Research On Modeling And Solution Method Of Operational Tasks Optimization, Yue Ma, Lin Wu, Yun Liu, Guangzhao Ding

Journal of System Simulation

Abstract: Aiming at the problem of tasks optimization in operation task planning, this paper defines an operational tasks graph based on property graph and influence network to describe tasks, effects and their relationship. The model of operational tasks optimization is constructed based on the operational tasks graph, and the effect network transmission algorithm and resource constraint judgment algorithm are proposed. The problem is solved by the improved differential evolution algorithm. The experimental result shows that the operational tasks graph can vividly describe the relationship between operational tasks and effects, and the model and solution method are feasible and effective.

Multi-Objective Optimization Algorithm Based On Multi-Index Elite Individual Game Mechanism, Xu Wang, Weidong Ji, Guohui Zhou, Jiahui Yang

Journal of System Simulation

Abstract: In order to improve the convergence of multi-objective optimization algorithm and the diversity of optimization solution set, and alleviate the flown down of population in target space, a multi-objective optimization algorithm based on multi-attribute elite individual game mechanism is proposed. This paper uses Pareto dominance relationship and multi-index to comprehensively screen elite individuals. The elite individual game mechanism with K-means clustering is integrated with cross and mutation strategy, which effectively improves the convergence and diversity of the algorithm. A detailed convergence analysis of the algorithm is performed to prove the convergence of the algorithm. Eight representative comparison algorithms are …

Research On Decision Behavior Modeling Method Of Key Figures, Xiao Zheng, Xiaodong Peng, Minyu Lu, Tiejun Liu

Journal of System Simulation

Abstract: The decision-making of key figures is an important factor affecting the evolution of concerned events. The research on their decision-making behavior is of great significance for the prediction of important events. For the problem of decision behavior modeling and decision propensity prediction of key figures, the character attribute and measurement methods required for character modeling are analyzed, the character decision-making process and decision-making related influencing factors are analyzed, the exploration research of decision propensity prediction method is carried out, and the prediction model of decision propensity based on comprehensive interest characteristics and psychological characteristics is constructed. Through the research …

Flexible Job-Shop Scheduling Problem Based On Improved Wolf Pack Algorithm, Chaoyang Zhang, Liping Xu, Jian Li, Yihao Zhao, Kui He

Journal of System Simulation

Abstract: An improved wolf pack algorithm is proposed for solving multi-objective scheduling optimization for flexible job shop problems. A multi-objective flexible job shop scheduling model is developed with the maximum completion time of the workpiece and the energy consumption of the machine as the optimization goals. An improved wolf pack algorithm is proposed for solving the shortcomings that traditional wolf pack algorithm is easy to fall into the local optimization. Through improving the intelligent behavior of the wolf pack algorithm, individual codes are designed from the two levels of job's process and machine, and POX(precedence operation crossover) cross operation is …

A New Electromagnetic Positioning Model With Single Coil Receiver For Virtual Interventional Surgery, Jianhui Zhao, Peijun Zhong, Zhiyong Yuan, Wenyuan Zhao, Tingbao Zhang

Journal of System Simulation

Abstract: To meet the needs of 3D positioning of guide wire catheter in interventional surgery and the requirements of smaller size sensor for narrow cerebral vessels, a new electromagnetic positioning model is proposed with single coil receiver. Based on the electromagnetic theory and geometry principle, the electromagnetic field transmitter with groups of three orthogonal coils and the single coil receiver with smaller size than existing sensors are designed. Based on Biot-Savart Law, the distance between receiving end and geometric center of orthogonal coils is calculated, and spatial coordinate of receiving end is computed based on the spherical intersection formula. To …

Calculation Of Optimal Vocs Emission Reduction Based On Improved Seirs Model In Cloud Environment, Guangqiu Huang, Xixuan Zhao, Qiuqin Lu

Journal of System Simulation

Abstract: Volatile organic compounds (VOCs) emissions in different regions are correlated and influenced. In order to minimize the impact of VOCs on the atmospheric environment and achieve synergistic governance of VOCs regions, an optimal emission reduction model is established with the maximum VOCs emission reduction as the primary goal. An improved SEIRS infectious disease dynamics optimization algorithm considering environmental pollution(SEIRS-CE) is proposed and the model is solved in cloud environment. Taking Xi'an city as an example, the SEIRS-CE algorithm is used in Ali cloud server to calculate the emission reduction of VOCs associated with 13 meteorological monitoring stations in Xi …

Process Automation And Robotics Engineering For Industrial Processing Systems, Drake Stimpson

USF Tampa Graduate Theses and Dissertations

Automation in industrial systems applications has emerged as the fundamental solution for improving quality, production rate, and efficiency of a process. Much of the recent popularity surrounding the transition of processes from manually operated tasks to automated systems can be attributed to the concept of Industry 4.0, which outlines the fundamental guidelines for integrating cyber-physical systems into industrial processes. Due to rapid advancement of technology in robotics and automation as well as the increase in accessibility of resources to this technology, the capability to develop automated systems has become feasible for small-scale enterprise. This work presents a two-part initiative to …

Optimizing Locations And Sizes Of Asphalt Concrete Plants In Karbala, Iraq, Ghayath Ali, Sawsan R Mohammad, Alaa M. Abdulhussein

Al-Bahir

This study develops and presents a methodology for determining the optimal geographic distribution and size of asphalt concrete plants in Karbala, Iraq, in order to minimize the cost of asphalt concrete produced. The purpose of this study is to discuss these points. The methodology can identify potential locations for asphalt concrete plants within a study area, considering the plants' operation and capital costs and the costs of transporting raw materials to the plants and asphalt concrete to demand centers. Matrix Laboratory (MATLAB) software have been used to program the methodology. This methodology has been applied to Karbala using actual data. …

The Impact Of Case Management Intervention For Insured Asthma Patients In Louisiana, An Empirical Study, Mohamed Mohamed Ohaiba

LSU Doctoral Dissertations

Asthma is a chronic condition whose symptoms are managed/prevented using medication and interventions. The overarching objective of this study was to evaluate the impact of patients' demographics on case management enrollment and healthcare utilization, as well as to develop machine learning models to predict high-cost patients.

To accomplish these goals, the Man-Whiteness test, the chi-squares test, logistic regression and odds ratios, and machine learning models were implemented. The average cost of the non-enrolled CM group was significantly higher than the enrolled group (p-value .0001). In addition, the non-enrolled groups had considerably more visits to the emergency department than the other …

Fast And Accurate 3d Object Reconstruction For Cargo Load Planning, Adam R. Nasi

Theses and Dissertations

Cargo load planning involves efficiently packing objects into aircraft subject to constraints such as space and weight distribution. Currently, this is performed manually by loadmasters. The United States Air Force is investigating ways to automate this process in order to improve airlift operational readiness while saving money. The first step in such a process would be generating 3D reconstructions of cargo objects to be used by a load planning algorithm. To that end, this thesis presents a novel method for fast, scaled, and accurate 3D reconstruction of cargo objects. This method can scan a 2.5m×3m×2m object in less than 10 …

A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

An efficient manufacturing system is key to maintaining a healthy economy today. With the rapid development of science and technology and the progress of human society, the modern manufacturing system is becoming increasingly complex, posing new challenges to both academia and industry. Ever since the beginning of industrialisation, leaps in manufacturing technology have always accompanied technological breakthroughs from other fields, for example, mechanics, physics, and computational science. Recently, machine learning (ML) technology, one of the crucial subjects of artificial intelligence, has made remarkable progress in many areas. This study thoroughly reviews how ML, specifically deep (reinforcement) learning, motivates new ideas …

Introduction To The Special Issue On Innovation In Transportation-Enabled Urban Services, Part 1, Niels Agatz, Soo-Haeng Cho, Hai Wang, Saif Benjaafar

Research Collection School Of Computing and Information Systems

Rapid developments in city infrastructure and technol-ogies are creating numerous opportunities and inspiring innovative and emerging urban services. Among these innovations, complex systems of urban transportation and logistics have embraced advances and have been reshaped significantly. They enable innovative new urban services, which are now booming and changing everyday life for urban residents.This special issue of Service Science explores perspectives on innovation in transportation-enabled urban services. We hope that the special issue will enhance the understanding of the planning, operation, and management of such services. Contributions are expected to demonstrate rigorous model development, economic/ econometric analysis, and decision-making tools based …

Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick

Theses and Dissertations

This research trains, tests, and analyzes bot and troll classification models using publicly available, open source datasets. Specifically, it applies decision tree, random forest, feed forward neural networks, and long-short term memory neural networks with hyperparameters tuned via designed experiment to five labeled bot datasets created between 2011 and 2020 and one dataset labeling state-sponsored disinformation accounts or trolls. The first three models utilize account profile features, while the last model applies natural language processing techniques, specifically GloVe embedding, to analyze a user’s Tweet history. Results indicate that the random forest model outperforms the other three models with an average …

Critical Infrastructure System Resiliency Modeling Using Multi-Layer Network Optimization, Spencer R. Figge

Theses and Dissertations

ccurately modeling the interdependent operation of critical infrastructure systems is an effective and efficient way of proactively evaluating system vulnerabilities and resiliency. Infrastructure systems are designed to transport essential commodities from where they are produced to where they are consumed and network flow-based models are one of the most effective ways to simulate and quantify infrastructure performance. The literature is populated with proposed models that must balance accuracy of interdependent operations, capability to include real-world considerations, and computational cost. This research proposes an alternative network-flow based model called the Critical Infrastructure System Resiliency Model (CISRM) that focuses on modeling a …

Investigation Of Rhine Pointing As A Solution To The Aircraft Human Machine Interface Problem, Alexandra C. Dobranski, Samuel J. Medvec

Theses and Dissertations

The human machine interface in 5th generation aircraft has not evolved proportionally with advances in display size and data density. The traditional cursor slew method fails to rapidly relocate the cursor, especially on large displays. Previous studies at the Air Force Test Pilot School and Air Force Institute of Technology identified methods that have the potential to improve the human machine interface. This research expanded upon those studies by providing an assessment of head tracking technology as a secondary method of cursor manipulation. Specifically, this study examined the effects that visual feedback (visible and invisible head tracking cursors) and cursor …

Long-Term Asset Prioritization To Support District Planning, Melissa R. Sallberg

Theses and Dissertations

The United States Air Force (USAF) relies on its installations to project military power across the globe. However, due to the deferred infrastructure maintenance and recapitalization backlog of $33 billion as of 2019 (Wilson & Goldfein, 2019), it is more critical than ever for base-level community planners to focus their attention to the projects that will achieve each installation’s long-term goals. The recent incorporation of asset management principles into the USAF District Planning Process allows a unique opportunity to improve the existing scoring model for a holistic look at what matters to enterprise leaders and community planners making the plans …

Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston

Theses and Dissertations

Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …

An Analysis Of Aircraft Maintenance Leading Indicator Metrics To Unit-Level Aircraft Availability Rates, William C. Hardy

Theses and Dissertations

The purpose of this research is to improve the usefulness of data that is already collected within aircraft maintenance organizations to better identify trends, and outliers, and possibly better explain relationships between leading and lagging indicator metrics. Specifically, this graduate research paper sought to answer two research questions addressing what aircraft maintenance metrics significantly impact aircraft availability, and how to measure those to understand which metrics impact aircraft availability most. The research questions were answered through a comprehensive literature review, and the use of multiple linear regression analysis on data from two specific aircraft maintenance organizations from the same location. …

Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim

Theses and Dissertations

A post-traumatic headache (PTH), resulting from a mild traumatic brain injury (mTBI), potentially develops into persistent post-traumatic headache (PPTH). Although no known cure for PPTH exists, research has shown that receiving treatment at earlier stages of PTH lowers the risk of patients developing PPTH. Previous studies have shown machine learning (ML) models capable of predicting a patient’s PTH progression, but none have considered the issue of protecting patient privacy. Due to patient privacy, ML models only have access to data within the institution. Federated learning (FL) harnesses data from separate institutions without sacrificing patient privacy as institutions can run ML …

Pattern Of Life Modeling On Maritime Vessels With Bayesian Inferencing, Miles A. Kelly

Theses and Dissertations

Despite decades of research, maritime traffic models’ limited predictive power continues to constrain their operational utility. We build on previous pattern of life modeling algorithms and contribute a Bayesian inferencing model for anomaly detection. Our probabilistic approach provides decision makers the capability to tailor the belief threshold for identifying anomalies and to enact a measured response based on the degree of abnormality. We perform a case study to evaluate the results, verifying that our Bayesian inferencing method accurately refines its probability when given the location and time of a ship of interest, and serving as a proof of concept for …