Operations Research, Systems Engineering and Industrial Engineering Commons^™

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 …

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 …

Hybrid System Simulation Method Based On Quantized State, Zhihua Li, Jiang De, Hanwu Shen, Zhihua Fan

Journal of System Simulation

Abstract: Hybrid system simulation and discontinuity processing have always been the difficulties of the time-discretized integration methods, while Quantized State System (QSS) is a new numerical integration method based on state variable discretization. Aiming at the hybrid systems simulation, a method of QSS+DEVS is proposed. The discrete part of hybrid system is represented as DEVS model, and the continuous part of hybrid system is discretized by QSS, which can also be represented as DEVS model. The simulation model of the whole hybrid system is obtained by coupling the two DEVS models. The accuracy, efficiency and simplicity of the QSS+DEVS method …

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 …

Actuator Fault Status Evaluation Based On Two-Class Nmf Network, Yinsong Wang, Tianshu Sun

Journal of System Simulation

Abstract: In the feedback control loop, the adjustment ability of controller covers up the performance degradation of the actuator to some degree. A fault state evaluation algorithm based on a two-class non-negative matrix network is proposed to implement online fault state monitoring of the actuator, including fault classification and degradation assessment. The local static features of the samples are extracted, and a classifier model is established to form a network. The similarity is introduced to describe the dynamic characteristics between samples. To fulfill the actuator fault status assessment, the static distance and dynamic changes of the network output are merged …

The Research And Implementation Of Film Virtual Photography Harware-In-The-Loop Simulation, Baihong Lu, Jianjun Zhao, Gesan Liu

Journal of System Simulation

Abstract: Film virtual photography is an important part of the film virtual Previs. Aiming at the problems of high cost, poor user experience, and bad simulation of existing virtual photography, a hardware-in-the-loop simulation system for film virtual photography is proposed. It uses a hardware-in-the-loop simulation virtual photography module that is consistent with the operation method of the film creator in real shooting for virtual photography, which solves the problems of difficult virtual photography operations and not in line with the real operating habits in the past. It provides a virtual photography method that is more in line with movie …

Passenger Flow Sensitivity Analysis Of Evacuation Time For Standard Subway Station, Guoao Zhang, Ma Si, Wang Lin

Journal of System Simulation

Abstract: Underground two-level island platform stations widely existed in urban rail transit system. In order to analyze the relationship between the evacuation time and the character of passenger flow, the capacity of main evacuation facilities and the evacuation bottleneck of stations are studied, and groups of sensitivity analysis experiment are designed. The variability of the evacuation process is analyzed by comparing the output of each simulation model in a group and between groups. The simulation result shows that the station evacuation time increases within a certain limit at peak hour. And the station evacuation time is mainly affected by the …

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, …

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 …

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 …

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 …

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 …

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, …