Operations Research, Systems Engineering and Industrial Engineering Commons^™

Carbon Nanotori Reinforced Lubricants In Plastic Deformation Processes, Jaime Taha-Tijerina, Juan Manuel Martinez, Daniel Euresti, Patsy Yessenia Arquieta-Guillen

Manufacturing & Industrial Engineering Faculty Publications

This research presents the effects of carbon nanotori structures (CNst) dispersed as reinforcement for metal-working and metal-forming lubricants. Synthetic (SL) and deep drawing (DD) nanolubricants were prepared following a two-step method at 0.01 wt.%, 0.05 wt.%, and 0.10 wt.% filler fractions. Slight increases in viscosity (oz) increased by 16% and 22% at merely 0.01 wt.% CNst reinforcement and up to 73% and 107% at 0.10 wt.% filler fraction for SL and DD nanolubricants, respectively, compared to conventional materials. Additionally, at 0.10 wt.% wear scar evaluations showed a highest benefit of 16% and 24%, for SL and DD nanolubricants, respectively. This …

Optimization Of Dynamic Post-Disaster Emergency Distribution Network Under Perspective Of Rescue Efficiency, Xinyu Gao, Jing Ni

Journal of System Simulation

Abstract: Aiming at the emergency rescue, a dynamic directed rescue network is established with the dynamic changes of the location, demand, and affected population of disaster site, and a mathematical model is constructed with the maximum rescue efficiency. A data envelope analysis model is applied to evaluate the efficiency of each rescue route segment. An efficiency-based dynamic routing model is established to transform the dynamic routes into the multi-stage static routes through the time slice division. An improved hybrid greedy-ant colony optimization algorithm is designed to solve the model, and the proposed algorithm is compared with the genetic algorithm, particle …

Optimal Operation For Park Integrated Energy System Considering Interruptible Loads, Lixin Ma, Ying Cheng

Journal of System Simulation

Abstract: The operating mode of thermal power generation units has certain limitations in peak shaving capacity. Interruptible load (IL), as a power resource to be tapped, can be applied to the park integrated energy management and microgrid systems to guide users to reduce peak electricity consumption. The IL function is introduced into the park integrated energy system with combined heat and power units to improve the system's peak shaving ability, and the corresponding model is established with the optimization goal of economy. Taking an ecological park of northern region as the example, the adaptive chaotic particle swarm algorithm is used …

Idea Of Infinitesimal Method-Introduced Hybrid Tt&C Resources Joint Scheduling, Naiyang Xue, Dan Ding, Hongmin Wang, Yile Fan, Zhongqian Liu

Journal of System Simulation

Abstract: Aiming at the study on the motion performance of a two-dimensional variable stiffness snake-robot, a Simulink/Adams co-simulation model is established, and the effects of the damping coefficient, the stiffness parameters and the angular frequency of the variable stiffness actuator on the motion energy consumption are analyzed. To realize the synchronous control of joint trajectory and stiffness, a motion controller based on two-layer CPG is proposed. The results show that the damping coefficient can effectively reduce the proportion of starting energy consumption of the variable stiffness snake-like robot, and the ratio of starting energy consumption increases with the stiffness parameter …

Radar Remote Sensing Data Augmentation Method Based On Generative Adversarial Network, Xu Kang, Xiaofeng Zhang

Journal of System Simulation

Abstract: In the research field of radar remote sensing, both the completeness and diversity of radar data samples cannot meet the requirement of effective training of deep learning models, and the models are prone to over-fitting, which significantly limits the wide application of deep learning techniques in this field. Targeting on the needs of intelligent application in radar remote sensing, a microwave imaging radar suited data augmentation method is proposed to solve the issue of insufficient radar data samples by leveraging the general framework of generative adversarial network. Aiming at the features of radar samples being not obvious, the label …

A Devs-Based Formal Description Method For Complex Product Behavior Models, Qingquan Lin, Jiaran Yang, Heming Zhang

Journal of System Simulation

Abstract: For the online optimization of pedestrian flow control in subway station, an algorithm frame for pedestrian flow control in subway station based on machine learning is designed. The pedestrian flow control process of a subway station during morning rush hour is selected,and the agent-based model is built to simulate the control process. The training data is collected through the multiple runs of the model, which is used as the input of deep reinforcement learning network, and the mature net is obtained through adequate training to provide the optimizing scheduling policy. Linking the actual data with the mature net …

Design And Development Of A Simulation System For Scheduling In Cloud Manufacturing Based On Microservice Architecture, Yongkui Liu, Ming Zeng, Lin Zhang, Jinwei Guo, Siyang Yuan, Yaoyao Ping

Journal of System Simulation

Abstract: In view of the lack of the low coupling and highly extensible cloud manufacturing scheduling simulation system, that leads to inconvenience of the performance test on scheduling algorithms, a scalable cloud manufacturing scheduling model with the scheduling goal of the minimization of cost and completion time and the maximization of quality of service is proposed. A micro-service architecture based cloud manufacturing scheduling simulation system is designed and developed, which realizes the functions of system management, resource management, task management and simulation management, and has the characteristics of flexible autonomy, stability and scalability. The simulation system facilitates the …

Motion Simulation And Performance Analysis Of 2d Variable Stiffness Snake-Like Robot, Yanqin Long, Guifang Qiao, Guangming Song, Ying Zhang, Linlin Cheng

Journal of System Simulation

Abstract: Mutual interference of vehicular laser radar causes serious performance reduction of target detection and tracking. From spatial, time and modulation frequency, various possible interference of lidars of pulse and frequency modulated continuous wave method in road environments are studied by simulation. The possibility of the interference is calculated, the features and performance reduction of the interference are analyzed. For the possible interference, using a method of pseudo random noise code to modulate the output amplitude of the continuous wave laser can effectively reduce the probability of interference and ensure the reliable operation of lidar in road environments.

Design And Implementation Of A Hybrid Solver On Cpu And Gpu Multi-Target Machines, Lin Ma, Xuesong Zhang, Xinlin Lei, Tie Bao

Journal of System Simulation

Abstract: The traditional parallel solving methods for the ordinary differential equations mainly include the task-oriented parallelism and the method-oriented parallelism. However, these two solving algorithms have serious shortcomings, which can only use CPU resource or just design for the homogeneous form of ODE(ordinary differential equations) clusters. By using RIDC(revisionist integral deferred correction) algorithm, a hybrid solver based on CPU and GPU multi-target machine is designed, which solves the differential equation system based on the pipeline form. Meanwhile, the parallel calculation within a single equation group and between the different equation groups is realized, which can give full play to the …

Indoor Positioning Algorithm Based On Xgboost Prediction And Elastic Net Error Compensation, Xiaofei Kang, Xuan Zeng, Wei Qiao

Journal of System Simulation

Abstract: Aiming at the multi-depot half-open vehicle routing problem and consideringthe soft time window constraints and vehicle speed changes, an optimization model with the goal of maximizing average customer satisfaction, shortest distribution distance and minimum distribution cost is established and a two-stage solution algorithm is designed. The self-adaptive grid density method and neighborhood crowding density method are used to maintain the external archives and to select the global optimal particles, and the convergence of the multi-objective particle swarm optimization (MOPSO) and the diversity of the later population can be improved to obtain the initial feasible solution. The initial feasible …

Feature Matching Algorithm Based On Optimal Geometric Constraints And Ransac, Xiaojuan Ning, Jieru Li, Fan Gao, Yinghui Wang

Journal of System Simulation

Abstract: In order to solve the problem that it's hard to reconcile the quality and computational efficiency of feature point matching. The initial matching for the extracted feature points is implemented through k-nearest neighbor (KNN) algorithm. According to the characteristics of equal length and same slope of the connecting line between matching points, the optimal geometric constraint is constructed based on the statistical sorting strategy to eliminate the obvious matching errors. Then random sample consensus (RANSAC) algorithm is utilized for further filtering to ensure the accuracy of the feature matching point pairs. Experimental results show that the method can obtain …

An Unmanned Swarm Search Method Based On Human-Robot Cooperation, Xin Zhou, Weiping Wang, Yifan Zhu, Tao Wang, Tian Jing

Journal of System Simulation

Abstract: Human-robot collaboration is a research hotspot and the human and unmanned swarm collaborative search is a typical scenario. It can carry out the more complex tasks by combining the human complex reasoning capabilities with repeated and precise execution capabilities of unmanned swarm. Based on the high-value target search of the uncertain scenarios, the concept definition for the collaborative search of human and unmanned swarm is given. A multi-agent dynamic programming model under uncertain with unknown prior knowledge is proposed, established to describe how the multi-agent system carries out the search under human support. A dynamic programming algorithm …

Research On Multi-Depot Half-Open Vehicle Routing Problem With Time-Varying Speed, Kaiqing Zhang, Qichun Ji

Journal of System Simulation

Abstract: Based on the analysis of operation concept and its elements, this paper proposes a framework of operation effectiveness simulation evaluation under the guidance of operation concept. Based on this framework, the basic idea of operation effectiveness simulation evaluation index construction under the guidance of operation concept is put forward. The specific methods of operation task modeling based on description, operation activity modeling based on decomposition, and operation effectiveness index selection based on effect are studied. The operation effectiveness simulation evaluation index system is constructed by taking the ground assault unit mountain key point capture and attack operation task guided …

Continuous Simulation Technology For Multi-State Evolution Of Urban Road Traffic, Qinglu Ma, Lin Zhang, Xinxin Yuan, Fengjie Liu

Journal of System Simulation

Abstract: Arming at the decreased positioning accuracy caused by the environment dynamic change of indoor positioning system, an error compensation algorithm based on XGBoost fusion elastic net is proposed. XGBoost positioning model is used to make a preliminary prediction on the target position. When the indoor environment changes, the elastic net algorithm is used to construct an error compensation model to correct the positioning error of XGBoost positioning model. The experimental results show that when only 15% of the fingerprint database samples need to be updated, the positioning accuracy of the proposed algorithm is controlled in 0.73m at the 80% …

Research On Space Launch Visualization Simulation Analysis Technology And Application, Feng Wu, Xiuluo Liu, Jia Wang, Yang Liu, Sujiang Li, Yan Zhong

Journal of System Simulation

Abstract: Through the typical cases in the field of military, society, manufacturing etc., this paper introduces the concept and features of complex engineering system of systems as well as the significance of modeling and simulation for the study of complex engineering system of systems. Taking complex product manufacturing as an example, the evolution process from systems engineering to model-based systems engineering (MBSE) and then to modeling and simulation-based system of systems engineering is analyzed. The characteristics and challenges of modeling and simulation of complex engineering system of systems is discussed. Some research topics in filed of MSBS2E is introduced, which …

Simulation On Critical Conditions Of Delay Diffusion In Scale-Free Logistics Network, Hongguang Yao, Huihui Xiao, Hang Zhang

Journal of System Simulation

Abstract: Aiming at the critical condition of delay diffusion in scale-free logistics network, a susceptible-infected-susceptible(SIS) model based on the density of delay nodes is established by mean field theory, and the critical value is solved. By designing the delay diffusion simulation system in logistics network, a virtual network with scale-free attribute is generated, and the critical condition is verified by simulation. The results show that there are a few key nodes with high value in scale-free logistics network. Once these nodes have service obstades, compared with other nodes, it will lead to a larger range of delay and faster …

Hybrid Variable Neighborhood Search Algorithm For The Multi-Trip And Heterogeneous-Fleet Electric Vehicle Routing Problem, Weiquan Wang, Ding Ding, Shuyan Cao

Journal of System Simulation

Abstract: Based on the real business practice, the multi-trip and heterogeneous-fleet electric vehicle routing problem (MTHF-EVRP) with time windows in green logistics is studied. A path-based mixed-integer linear model is built for the precise solution to the small-scale instances. A hybrid variable neighborhood search algorithm (Hybrid VNS) combined the variable neighborhood search algorithm with the labeling algorithm is proposed for the large-scale instances. The algorithm generates a modified insertion heuristic with random factor to construct the initial solution, allows the time window and range violation, adopts the neighborhood operators for the local search, and applies a labeling algorithm to solve …

A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez

LSU Doctoral Dissertations

In this research, we investigated the application of deep reinforcement learning (DRL) to a common manufacturing scheduling optimization problem, max makespan minimization. In this application, tasks are scheduled to undergo processing in identical processing units (for instance, identical machines, machining centers, or cells). The optimization goal is to assign the jobs to be scheduled to units to minimize the maximum processing time (i.e., makespan) on any unit.

Machine learning methods have the potential to "learn" structures in the distribution of job times that could lead to improved optimization performance and time over traditional optimization methods, as well as to adapt …

An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

Given n demand points in a geographic area, the elliptical cover problem is to determine the location of p depots (anywhere in the area) so as to minimize the maximum distance of an economical delivery trip in which a delivery vehicle starts from the nearest depot to a demand point, visits the demand point and then returns to the second nearest depot to that demand point. We show that this problem is NP-hard, and adapt Cooper’s alternating locate-allocate heuristic to find locally optimal solutions for both the point-coverage and area-coverage scenarios. Experiments show that most locally optimal solutions perform similarly …

Advancements Of Autonomous Applications, Jessica Massey, Jeremy Evert

Student Research

This material is based upon work supported by the National Aeronautics and Space Administration under Grant Agreement No. 80NSSC20M0114 issued through Oklahoma Space Grant Consortium. This research is in support of the Fire Dawgs competition team for this year’s SpeedFest competition at Oklahoma State University. This NASA OK Space Grant Consortium funded competition team will compete in the Charlie Class, where an autonomous vehicle will navigate a course and put out a fire.

Robots and self-driving vehicles are useful, especially for hazardous jobs, such as firefighting. The use of high-tech sensing technology is a small part of how self-driving vehicles …

A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert

Student Research

Machine learning is becoming very popular in many technological aspects worldwide, including robotic applications. One of the unique aspects of using machine learning in robotics is that it no longer requires the user to program every situation. The robotic application will be able to learn and adapt from its mistakes. In most situations, robotics using machine learning is designed to fulfill a task better than a human could, and with the machine learning aspect, it can function at the highest level of efficiency and quality. However, creating a machine learning program requires extensive coding and programming knowledge that can be …

A Discussion On Supplier Selection Modeling Approaches, Sheida Etemadidavan, Andrew J. Collins

Modeling, Simulation and Visualization Student Capstone Conference

Supplier selection is a subfield of supply chain management that involves multiple steps in order for decision-makers to find suitable suppliers. Supplier selection is important as it could influence the whole company positively or negatively. It has, recently, become a topic of interest because of the recent pandemic and its effect on the global supply chain, which causes supply shortages. As such, the focus of this paper is on characteristics of decision-making modeling approaches, specifically agent-based modeling and multi-agent systems, in supplier selection, as its modeling has always been a challenge for companies due to its complex nature.

Risk-And-Resiliency-Intelligent Supply Chain (Rrisc), Ahmad A. Abdelnabi, Ahmed M. Abdelmagid, Ghaith Rabadi, Andres Sousa-Poza, C. Ariel Pinto

Modeling, Simulation and Visualization Student Capstone Conference

This work proposes a risk-and-resiliency-intelligent supply chain (RRiSC) tool which is an SC risk management framework that leverages cutting-edge technologies in Artificial Intelligence (AI), Big Data Analytics (BDA), and Digital Twins (DT) to develop specific capabilities for SC risk management. RRiSC is a convergence of mature tools and techniques embedded in three modules: Modeling, Simulation, and Visualization – all together integrate the optimization, simulation, and data analytics to test the performance of the whole supply network under different scenarios through measuring the vital KPIs, identifying the vulnerabilities, and setting proactive plans to diminish risks consequences.

Is Explainability Always Necessary? Discussion On Explainable Ai, Gayane Grigoryan, Andrew J. Collins

Modeling, Simulation and Visualization Student Capstone Conference

The explainability of a model has been a topic of debate. Some research states explainability is unnecessary, and some ”white-box” models, such as regression models or decision trees, are inherently explainable. This paper conducts a multiple regression model analysis with highly correlated features to illustrate how the model’s explainability fails when dealing with complex data. In this case, trusting the model explanations can be problematic. The Shapley net effect technique, which helps determine the marginal contribution of the features, is employed to improve the model explainability and reveal more information about the prediction. The work concludes that explainability is necessary …

21st Century Leadership: Leadership In Challenging Times, Adam Morris

Operations Management Presentations

Our global society has experienced unprecedented changes in the last couple years. The COVID-19 pandemic created drastic changes to our personal and professional lives. We went to a virtual work and learning environment almost overnight. People in leadership positions had to make impossible decisions on items no one has ever experienced. With all the changes that are happing in our world, what does it take to be a leader in today’s global society? Do basic leadership principles from 30 years ago still apply? Watch the latest installment of the MSEM/MSOM Lunch & Learn Webinar Series that will discuss these leadership …

Lyapunov-Based Economic Model Predictive Control For Online Model Discrimination, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Economic model predictive control (EMPC) is a flexible control design strategy that can be modified to achieve many operating goals while also ensuring safe operation (e.g., by adding Lyapunov-based stability constraints to form Lyapunov-based EMPC, or LEMPC). Prior works have investigated LEMPC capabilities for achieving goals online beyond optimizing process economics, including aiding in model structure selection to benefit model-based control system design since the accuracy and quality of the process model are important for achieving an expected performance from such systems. This work further probes the capabilities of LEMPC to accomplish multiple objectives during process operation, including aiding in …

Financial Analysis Of Meta Platforms Inc, Anurag Yaddanapudi, Kaushik Chaudhary, Saumya Saxena

Engineering and Technology Management Student Projects

Web3.0 is the latest generation of internet, which is about decentralization and democratization, built on blockchain technology, high computer power and high-speed network. Metaverse overlaps with Web3.0 in terms of decentralization and is built on the same base technologies but talks about virtual realities and brings immersive experiences.

This study explores how the web has evolved over the years and analyzes the current market trends of Web3.0. The purpose of the study is to examine the investments made by Meta Platforms Inc. which is one of the market leaders of the Internet industry and provide an in-depth financial analysis by …

Society Dilemma Of Computer Technology Management In Today's World, Iwasan D. Kejawa Ed.D

School of Computing: Faculty Publications

Abstract - Is it true that some of the inhabitants of the world’s today are still hesitant in using computers? Research has shown that today many people are still against the use of computers. Computer technology management can be said to be obliterated by security problems. Research shows that some people in society feel reluctant or afraid to use computers because of errors and exposure of their privacy and their sophistication, which sometimes are caused by computer hackers and malfunction of the computers. The dilemma of not utilizing computer technology at all or, to its utmost, by certain people in …

Modular And Deployable Solution For Passing Hazardous Roads, Nicholas Short

LMU Theses and Dissertations

The developing world often relies on low-water crossings on unpaved roads in place of bridges for vehicle river crossings and impoverished communities suffer disproportionately more from road shut-downs. This project defines a modular and deployable bridge solution to combat low-water crossing hazards in undeveloped road systems in year-round conditions using Systems Engineering and related methodologies to architect the solution.

Designing For The Future: Sensor And Gauge Assembly Work Cell Design, Kaitryana Leinbach

Honors Capstones

No abstract provided.