Operations Research, Systems Engineering and Industrial Engineering Commons^™

Application Of Trust Driven Adaptive Cooperative Control Algorithm, Xindong Gui, Hongjiang Ji, Lingling Fan, Shida Liu

Journal of System Simulation

Abstract: When a multi-manipulator performs cooperative task, it's end position is difficult to accurately track the target and ensure the consistency influenced by the nonlinear factors such as working environment, assembly condition and system disturbances, resulting in large errors during collaborative work. To solve multi-manipulators position coordinated control problem, a multi-agent based adaptive position coordination control algorithm is proposed by researching on the novel trust mechanism, including adaptive update mechanism of trust value (self-trust and mutual-trust) and Fisher information weighted (covariance) update mechanism. In automated collaborative assembly tasks, the precise consensus positioning of end-effector is achieved with improvements in the …

A Signal Decomposition Method Based On Multi-Layer Iteration Structured Singular Spectrum Analysis, Yumiao Wei, Zhili Zhang, Hongguang Li, Shuqing Li

Journal of System Simulation

Abstract: To process the complex signals with concentrated frequency distribution, an adaptive decomposition method based on singular spectrum analysis with multi-layer iteration structure is researched. The traditional singular spectrum analysis is improved by frequency band subdivision and iterative filtering approach. A high-precision decomposition algorithm base on recursive structure is therefore designed, solving the problems such as insufficient adaptive capability and unsatisfied decomposition. Simulation results show that adaptive decomposition capability of the proposed method is effectively enhanced. For the multi-mode vibration signal with 0.2% ratio of spitting frequency to center frequency, the components are all accurately extracted, and consistent well …

Simulation Analysis Of Assessment Method For Missile Accuracy, Shuqing Li, Zhili Zhang, Yumiao Wei, Haitao Wang

Journal of System Simulation

Abstract: The missile accuracy of the falling points is one of the important performance indexes of missile systems, so the assessment method is very important. An improved algorithm for missile accuracy assessment is proposed. Accuracy assessment problem is simplified as a hypothesis check for probability circle, and the accuracy difference coefficients are defined to describe the accuracy difference between the real falling points and the expected situation. Based on the probability circle method, an improved risk assessment method is put forward to balance and minimize producer's risk and consumer's risk. According to sequential check method, this risk assessment …

Obstacle Avoidance Path Planning Of Bridge Crane Based On Improved Rrt Algorithm, Zhimei Chen, Li Min, Xuejuan Shao, Zhicheng Zhao

Journal of System Simulation

Abstract: In view of the problem that the reasonable path can not be obtained quickly for bridge crane planning in complex environment, a rapidly exploring random tree (RRT) algorithm combined with particle swarm algorithm is proposed. According to the characteristics of the bridge crane operation, the RRT algorithm is improved. The two-way RRT algorithm is used to make the tree grow in the direction of the target according to the probability. When the path is generated, the particle swarm optimization algorithm is used to smooth the path to get a more suitable path for the operation of the bridge crane. …

Cloud Model Pid Control Of Pmsm Based On Svm Inverse System, Li Hui, Yun Hao, Hongli Yue

Journal of System Simulation

Abstract: Aiming at the problem of multivariable, nonlinearity and strong coupling of the permanent magnet synchronous motor(PMSM), a strategy of inverse system identification which is independent of precise mathematical model and parameters based on support vector machines(SVM) is proposed. The dynamic decoupling control of PMSM is researched based on multivariable nonlinear control inverse system theory. To deal with direct inverse control open-loop system with poor robustness and inverse modeling error of SVM, a parameter self-tuning PID(Proportional Integral Differential) closed-loop controller based on cloud model rule inference is designed. The simulation results confirm that the cloud model PID control based on …

Combination Weighting-Based Comprehensive Evaluation For Discrete Workshop Production Plan, Zhangzhen Luo, Haifan Jiang, Jianlin Fu, Guofu Ding

Journal of System Simulation

Abstract: Aiming at the lack of a general evaluation index system and a comprehensive evaluation method combining qualitative and quantitative for discrete workshop production planning, an evaluation index system is constructed from the economy, timeliness and adaptability and a combination weighting-based comprehensive evaluation method is proposed. A combination weight of subjective and objective significance is obtained by combining the extension of analytic hierarchy process, entropy value method and improved CRITIC (Criteria Importance Through Intercriteria Correlation) method, which improves the scientific evaluation of discrete workshop production planning. The verification results of examples show that the method is more sensitive to the …

Short-Term Power Load Forecasting Based On Lstm Neural Network Optimized By Improved Pso, Tengfei Wei, Tinglong Pan

Journal of System Simulation

Abstract: To improve the accuracy of short-term power load forecasting, a short-term power load forecasting model (ACMPSO-LSTM) based on long-short memory neural network (LSTM) optimized by adaptive Cauchy mutation particle swarm optimization (ACMPSO) is proposed. For the problem of difficult selection of LSTM model parameters, ACMPSO is used to optimize model parameters, and non-linear changing inertia weights are adopted to improve the global optimization ability and convergence speed of PSO algorithm. In the optimization process, a mutation operation based on genetic algorithm is added to reduce the risk of particles falling into local optimal solutions. The simulation results show that …

Mpc Algorithm Design Based On Improved Macroscopic Traffic Flow Model, Hongguang Pan, Gao Lei, Wenyu Mi

Journal of System Simulation

Abstract: In order to obtain stable and orderly traffic flow, a model predictive control method based on improved macroscopic traffic flow model is proposed for highway system. Considering the uncertainty caused by the inflow and outflow of ramp, the method takes the traffic density and velocity of each section as the control target. Based on the traditional macroscopic traffic flow model, a macroscopic traffic flow state space model is improved. Aiming at the problem of multiple variables and control constraints, a traffic flow density and velocity controller based on model predictive control is designed to ensure better control effect. The …

Method Of Battlefield Frequency Allocation Based On Chaotic Perturbation Mechanism Particle Swarm Optimization Algorithm, Niu Kan, Li Bing, Fu Qiang

Journal of System Simulation

Abstract: In order to carry out the frequency allocation in the electromagnetic environment of battlefield and reduce the frequency equipment interference of various forces, a frequency allocation method based on chaotic perturbation mechanism particle swarm optimization algorithm is proposed. Which transforms battlefield frequency allocation into the optimal spectrum resource search and solution problem with constraints. The frequency allocation model with the lowest interference cost is built and the frequency allocation through the improved particle swarm optimization algorithm is carries out. The chaotic perturbation mechanism is introduced to improve the population diversity and the global optimization ability of the …

Sar Imaging Seeker Interference Modeling & Evaluation And Simulation System Design, Xueping Luo, Yunhe Cao, Hu Qi, Shutao Chen, Shijie Yan, Cai Xi

Journal of System Simulation

Abstract: For the simulation, evaluation and verification of SAR imaging seeker interference, the modeling and evaluation of SAR imaging seeker interference and design of simulation system are discussed. The simulation system can be used to model and simulate the target environment, jamming and seeker at the signal level. The signal environment simulation, echo signal acquisition, signal processing and other processes can be simulated under the environment of multiple interference signals, and the interference effect can be evaluated at the same time. The validity and practicability of the simulation system are verified with simulation test. The design of this simulation system …

Game Analysis Of Government Procurement Contract Financing Based On Blockchain Technology, Haitao Huang, Qinming Liu, Chunming Ye, Chen Xiang

Journal of System Simulation

Abstract: Abstract: In view of the financing difficulties of small and medium-sized enterprise and the existing credit problems of financial supply chain, the block chain technology is applied to the financing mode of government procurement contract of the Ministry of Finance. From the supply chain business aspect, the tripartite game model of government procurement departments, small and medium-sized enterprises and banks is built, and the decision of the main body is analyzed. From the block chain technology, the evolutionary game model is built and the selection of chain node is analyzed. By MATLAB, the simulation experiments are carried out to …

Residential Demand Response Scheduling Optimization And Simulation Based On An Improved Pso Algorithm, Huazhen Li, Youquan Liu, Jiawei Zhu, Liao Qiang

Journal of System Simulation

Abstract: Aiming at the problems of low utilization rate of household load energy and the potential damage to the power grid caused by the lack of systematic and efficient management of household power consumption, the power consumption characteristics of controllable equipment and the energy storage characteristics of electric vehicles are modeled respectively, and the scheduling optimization objective function of household equipment under time of use price is established, and the improved particle swarm optimization algorithm is used to solve the problem. Through the example simulation, the residential power dispatching under various scenarios is analyzed. The experimental results show that the …

Two-Point Joint Cpa Attacks Against Aes And Its Simulation, Tong Yu, Jingwen Cai

Journal of System Simulation

Abstract: Aiming at the problems of large sampling amount and low utilization rate of attack information in single-point power analysis attack, a method of two-point joint power analysis attack for AES (Advanced Encryption Standard) is proposed. This method selects two power leakage points for power analysis according to the correlation between the power leakage points and the key in the AES. By constructing a power leakage model of intermediate variables, an intermediate value joint function is established which means, the method can be used to recover the key of AES. The simulation results demonstrate that the attack time of …

Critical Chain – Or Why Wedding Planners Get Ulcers, Greg Hutto

Operations Management Presentations

Planning a wedding is one of the most challenging projects in a young life… So much to do! A respected journal in the project management literature -- Southern Bride -- advises well-off young couples to escape stress and employ a professional wedding planner+. In today's webinar we will contrast two project planning methods in examining one such wedding project -- hastily planned and beset with troubles. We will shed light on the science & art of project management and possibly help our wedding planners (both professional and amateur) avoid stress-induced medical complications. In this webinar, we’ll be spending time with …

Algebraic, Computational, And Data-Driven Methods For Control-Theoretic Analysis And Learning Of Ensemble Systems, Wei Miao

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we study a class of problems involving a population of dynamical systems under a common control signal, namely, ensemble systems, through both control-theoretic and data-driven perspectives. These problems are stemmed from the growing need to understand and manipulate large collections of dynamical systems in emerging scientific areas such as quantum control, neuroscience, and magnetic resonance imaging. We examine fundamental control-theoretic properties such as ensemble controllability of ensemble systems and ensemble reachability of ensemble states, and propose ensemble control design approaches to devise control signals that steer ensemble systems to desired profiles. We show that these control-theoretic properties …

Elucidating And Leveraging Dynamics-Function Relationships In Neural Circuits Through Modeling And Optimal Control, Sruti Mallik

McKelvey School of Engineering Graduate Student Theses & Dissertations

A fundamental research question in neuroscience pertains to understanding how neural networks through their activity encode and decode information. In this research, we build on methods from theoretical domains such as control theory, dynamical systems analysis and reinforcement learning to investigate such questions. Our objective is two-fold: first, to use methods from engineering to identify specific objectives that neural circuits might be optimizing through their spatiotemporal activity patterns, and second, to draw motivation from neuroscience to formulate new engineering principles such as synthesis of dynamical networks for decentralized control applications. We specifically take a top-down, optimization driven approach in our …

Analysis Of The Effects Of Spatiotemporal Demand Data Aggregation Methods On Distance And Volume Errors, Zachary Hornberger, Bruce A. Cox, Raymond R. Hill

Faculty Publications

Purpose — Large/stochastic spatiotemporal demand data sets can prove intractable for location optimization problems, motivating the need for aggregation. However, demand aggregation induces errors. Significant theoretical research has been performed related to the modifiable areal unit problem and the zone definition problem. Minimal research has been accomplished related to the specific issues inherent to spatiotemporal demand data, such as search and rescue (SAR) data. This study provides a quantitative comparison of various aggregation methodologies and their relation to distance and volume based aggregation errors. Design/methodology/approach — This paper introduces and applies a framework for comparing both deterministic and stochastic aggregation …

Augmenting The Space Domain Awareness Ground Architecture Via Decision Analysis And Multi-Objective Optimization, Albert R. Vasso, Richard G. Cobb, John M. Colombi, Bryan D. Little, David R. Meyer

Faculty Publications

Purpose — The US Government is challenged to maintain pace as the world’s de facto provider of space object cataloging data. Augmenting capabilities with nontraditional sensors present an expeditious and low-cost improvement. However, the large tradespace and unexplored system of systems performance requirements pose a challenge to successful capitalization. This paper aims to better define and assess the utility of augmentation via a multi-disiplinary study. Design/methodology/approach — Hypothetical telescope architectures are modeled and simulated on two separate days, then evaluated against performance measures and constraints using multi-objective optimization in a heuristic algorithm. Decision analysis and Pareto optimality identifies a set …

Cable Manipulation With A Tactile-Reactive Gripper, Yu She, Shaoxiong Wang, Siyuan Dong, Neha Sunil, Alberto Rodriguez, Edward Adelson

School of Industrial Engineering Faculty Publications

Cables are complex, high-dimensional, and dynamic objects. Standard approaches to manipulate them often rely on conservative strategies that involve long series of very slow and incremental deformations, or various mechanical fixtures such as clamps, pins, or rings. We are interested in manipulating freely moving cables, in real time, with a pair of robotic grippers, and with no added mechanical constraints. The main contribution of this paper is a perception and control framework that moves in that direction, and uses real-time tactile feedback to accomplish the task of following a dangling cable. The approach relies on a vision-based tactile sensor, GelSight, …

Evaluating Decision Making In Sustainable Project Selection Between Literature And Practice, Rakan Alyamani, Suzanna Long, Mohammad Nurunnabi

Engineering Management and Systems Engineering Faculty Research & Creative Works

A robust project selection process is critical for the selection of sustainable projects that meet the needs of an organization or community. There are multiple factors or criteria that can be considered in the selection of the appropriate sustainable project, but it can be challenging to find sufficient depth of expert opinion to perform a strong evaluation of these criteria. Several researchers have turned to the sustainable project literature as a source of expert opinion to evaluate the criteria used in sustainable project selection and rank them based on importance using different multi-criteria decision-making (MCDM) methodologies. However, using the literature …

Credit Assignment In Multiagent Reinforcement Learning For Large Agent Population, Arambam James Singh

Dissertations and Theses Collection (Open Access)

In the current age, rapid growth in sectors like finance, transportation etc., involve fast digitization of industrial processes. This creates a huge opportunity for next-generation artificial intelligence system with multiple agents operating at scale. Multiagent reinforcement learning (MARL) is the field of study that addresses problems in the multiagent systems. In this thesis, we develop and evaluate novel MARL methodologies that address the challenges in large scale multiagent system with cooperative setting. One of the key challenge in cooperative MARL is the problem of credit assignment. Many of the previous approaches to the problem relies on agent's individual trajectory which …

Machine Learning Framework For Nonlinear And Interaction Relationships Involving Categorical And Numerical Features, Shirish Mohan Rao

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Traditionally, physical scientific experiments have been conducted extensively to study and understand the behavior of a process or a system. With the advancement of computing technology in recent years, computer codes and algorithms are used as simulators to replicate behavior of a complex system. Such use of computers to study a system is termed as ‘computer experiments.’ The process involves selecting specific points or runs in the design space in order to maximize information about the system in minimal runs. These computer models are high dimensional and can take a long time to simulate. Metamodels (or surrogate models) built using …

Agent-Based Model Simulation For Police Deployment Decision-Making In Patrol Operations, Yasaman Ghasemi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Police patrolling plays a key role in responding to 911 calls and reducing crimes. The effectiveness of patrol operations heavily depends on the deployment of police officers – e.g., the number of officers assigned to specific policing districts or beats. The complex nature of the policing system – dynamic and stochastic criminal behavior, compounded with limited policing resources, render current (traditional) police operations, which are often managed in a reactive and stationary manner – often makes it very challenging to manage and control. This study develops an agent-based simulation framework to address the dynamically changing environment in police operations and …

Multistage Stochastic Programming: Algorithms, Modelling And Applications, Murwan Siddig

All Dissertations

This dissertation comprises four di˙erent topics related to multistage stochastic program-ming (MSP) algorithms, modeling, and applications.

First, we extend the adaptive partition-based approach for solving two-stage stochastic programs with a fixed recourse matrix and a fixed cost vector to the MSP setting, where the stochastic process is assumed to be stage-wise independent. The proposed algorithms integrate the adaptive partition-based strategy with a popular approach for solving multistage stochastic programs, the stochastic dual dynamic programming (SDDP) algorithm, according to two main strategies. These two strategies are distinct from each other in the manner by which they refine the partitions during the …

Micro Scalable Graphene Oxide Productions Using Controlled Parameters In Bench Reactor, Carolina S. Andrade, Anna Paula Godoy, Marcos Antônio Gimenes Benega, Ricardo J. E. Andrade, Rafael Cardoso Andrade, Wellington Marcos Silva, Josué Marciano De Oliveira Cremonezzi, Waldemar Augusto De Almeida Macedo, Hélio Ribeiro, Jaime Taha-Tijerina

Manufacturing & Industrial Engineering Faculty Publications

The detailed study of graphene oxide (GO) synthesis by changing the graphite/oxidizing reagents mass ratios (mG/mROxi), provided GO nanosheets production with good yield, structural quality, and process savings. Three initial samples containing different amounts of graphite (3.0 g, 4.5 g, and 6.0 g) were produced using a bench reactor under strictly controlled conditions to guarantee the process reproducibility. The produced samples were analyzed by Raman spectroscopy, atomic force microscopy (AFM), x-ray diffraction (XDR), X-ray photoelectron spectroscopy (XPS), Fourier-transform infrared spectroscopy (FTIR) and thermogravimetry (TGA) techniques. The results showed that the major GO product comprised of nanosheets containing between 1–5 layers, …

High-Density Parking For Autonomous Vehicles., Parag J. Siddique

Electronic Theses and Dissertations

In a common parking lot, much of the space is devoted to lanes. Lanes must not be blocked for one simple reason: a blocked car might need to leave before the car that blocks it. However, the advent of autonomous vehicles gives us an opportunity to overcome this constraint, and to achieve a higher storage capacity of cars. Taking advantage of self-parking and intelligent communication systems of autonomous vehicles, we propose puzzle-based parking, a high-density design for a parking lot. We introduce a novel method of vehicle parking, which leads to maximum parking density. We then propose a heuristic method …

Evaluation Of Patient Experience Using Natural Language Processing Algorithms, Sofia Veronica Ortega

Open Access Theses & Dissertations

INTRODUCTION: Healthcare organizations are making extensive efforts to improve the patient experience. Enhancing patient/client experience and outcomes is crucial for patient-centered care and can reveal improvement opportunities. Healthcare settings currently rely on surveys (e.g., HCAHPS) and patient feedback to measure patient experience. Studies have identified that utilizing patient journey mapping can better capture patient experience throughout all stages of the patient's journey and provide quality and process improvement recommendations at specific hotspots. However, these measurement techniques are time-consuming and resource intensive. AIM: This research aims to measure patient experience of breast cancer patients from social media data using natural language …

Machine Learning Models For Lodi Indices., Lucas A. Bruns

Electronic Theses and Dissertations

Two indices published monthly by the Logistics and Distribution Institute (LoDI) predict changes in logistics and distribution activity levels nationally and regionally and are useful for organizations when planning projects and expenses. This research validates the current linear regression model, updates the index conversion method, and introduces machine learning models.

New source data are introduced to the models to validate the current linear regression model and a comparative analysis verifies that the current source data are robust. A rolling average is used for index conversion in place of a fixed reference month to reflect recent changes in employment levels.

Three …

Shape-Based Time Series Mining For Process Monitoring And Anomaly Detection, Li Zhang

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Due to the rapid development of computing and sensing technology, Internet of Things (IoT)-enabled monitoring plays a crucial role for people suffering from cardiac problems. It is important to detect the abnormal ECG cycles during the cardiac monitoring for the early treatment. However, most existing methods focused on the full reading of time series, for the cycle-based time series, it is wasting time to read the whole time series while we can find the characteristic patterns instead. Characteristic patterns named shapelets are time series subsequences, which are explainable and discriminative features that can best classify time series. Shapelet-based classification that …

Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Many real world systems involve interaction among large number of agents to achieve a common goal, for example, air traffic control. Several model-free RL algorithms have been proposed for such settings. A key limitation is that the empirical reward signal in model-free case is not very effective in addressing the multiagent credit assignment problem, which determines an agent's contribution to the team's success. This results in lower solution quality and high sample complexity. To address this, we contribute (a) an approach to learn a differentiable reward model for both continuous and discrete action setting by exploiting the collective nature of …