Operations Research, Systems Engineering and Industrial Engineering Commons^™

Research On Time-Dependent Vehicle Routing Problem With Multiple Time Windows, Nan Li, Rong Hu, Bin Qian, Huaiping Jin, Naikang Yu

Journal of System Simulation

Abstract: Aiming at the time-dependent vehicle routing problem with multiple time windows (TD_VRPMTW) that considers urban traffic congestion, a hybrid discrete gray wolf optimizer (HDGWO) is proposed. In the HDGWO, a new grey wolf individual updating formula is designed, and the integer coding method based on customer permutation is adopted, so that the algorithm can directly perform the global search based on GWO individual updating mechanism in the discrete problem solution space.A population initialization strategy based on the nature of the problem is designed to generate the initial population with high quality and diversity.The information exchange formula of …

Rigid-Liquid Coupling Simulation Of Liquid-Filled Spacecraft Based On Openfoam, Zhijun Song, Zongyu Chen, Lü Jing, Tianshu Wang

Journal of System Simulation

Abstract: Aiming at the design of the spacecraft attitude control system, a simulation software for the rigid-liquid coupling calculation of the liquid-filled spacecraft is built on the basis of the open source CFD software OpenFOAM. In the moving boundary problem, the N-S equation in the non-inertial frame is derived to improve the calculation efficiency, which avoids a large number of grid conversion calculations of the moving grid method in the traditional CFD software. PIMPLE algorithm is used to build the sloshing dynamics solution module, and the variable step length Runge-Kutta method is used to build the attitude …

Effectiveness Evaluation Method Of Space-Based Information Systems Based On Sem, Chi Han, Wei Xiong, Wenwen Liu, Xiaolan Yu, Ping Jian

Journal of System Simulation

Abstract: Aiming at the nonlinear emergence of effectiveness of the coupling and interaction of space-based information system (SIS), an operational effectiveness evaluation (OEE) model based on structural equation modeling (SEM) is proposed. Through the analysis of capacity requirements and system composition, the internal connections of sub-systems are obtained, and the effectiveness evaluation index system is constructed. By considering the synergistic interaction within SIS, the linear and nonlinear SEMs are constructed respectively to evaluate the effectiveness, and the analytical model of OEE is established on the basis of the corresponding parameter equations. With the background of integrated joint operations under …

Bioinformation Heuristic Genetic Algorithm For Solving Tsp, Jia Xu, Fengqing Han, Qixin Liu, Xiaoxia Xue

Journal of System Simulation

Abstract: Genetic algorithm (GA) is one of the universal path optimization algorithms for traveling salesman problem (TSP). Aiming at the slow convergence and unstable solution of the traditional GA, a bioinformation heuristic genetic algorithm (BHGA) is proposed. By optimizing the fitness function and initial population, the gene sequence comparison technique in bioinformatics is introduced to carry out the cross recombination sorting. The gene reversal operation is used to implement mutation, to accelerate the convergence speed and get a better path solution. The numerical examples in TSPLIB database are solved by BHGA and the experimental simulation results show that the …

Design And Implementation Of Uav Swarm Self-Organizing Search Model, Kan Li, Yunpeng Li, Jiangbo Zhao

Journal of System Simulation

Abstract: The UAV swarm self-organizing search for moving target under the urban threat is an important implement of UAV swarm. Though Agent-based complex system modeling and simulation tools, the framework of UAV swarm search simulation model is constructed, and the self-organizing search model of UAV swarm is designed. Under the possible threats to the operational use of UAVs, the concept of self-organizing search for UAV swarm is preliminarily realized and demonstrated, and the solution of autonomous decision making for UAV swarm based on the probability-based finite state machine model is explored, which is analyzed and verified by a case. …

Servicing Method Of Lvc Experiment Resources Based On Object Metamodel, Nan Du, Yaxin Tan, Bin Feng

Journal of System Simulation

Abstract: In the process of live-virtual-constructive (LVC) experiment there are a large number of heterogeneous simulation resource objects. Aiming at the traditional object model not meeting the rapid response experiment requirements of equipment systems in informationized war, the object metamodel based on LVC experiment resource servitization method research is studied. The object metamodel based on resource description method is given, based on three basic resource servitization forms of object interaction, message passing, remote method invocation, virtualization infrastructure object(VIO), VIO-virtualization object model (VIO-VOM) components of publish/subscribe, VIO-VOM components of aggregation, composition, inheritance, callback mechanism, Localclass-VOM, Message-VOM components are proposed. The …

Development Of Vehicle Dynamics Virtual Simulation System Based On Carsim, Jianlei Liu, Xuejian Jiao, Huaiqian Wang

Journal of System Simulation

Abstract: Aiming at the "high cost, high consumption and high risk" of real vehicle test, a virtual simulation system of vehicle dynamics based on CarSim is developed. The real-time vehicle model is created by CarSim. A virtual scene is built in Unity3D, and an active stereoscopic display technology is used to realize the 3D visual effects. The driver's operation information is collected by simulating the steering wheel of Fanatec racing car and LabView, and the vehicle dynamics model is solved in NI-Pxie8840 controller to ensure the real-time operation. The calculated data is fed back to the driver through the six-degree-of-freedom …

Realization Of Domestic Ship Hydrodynamic Numerical Software On Industrial Cloud Platform, Yingyan Zhao, Qunsheng Cao, Zhengnan Cao, Jianchun Wang

Journal of System Simulation

Abstract: Developing the user-friendly cloud platform for high-performance numerical software deployment has great engineering significance. Based on the high performance computing resource of Web industry cloud platform, the large-scale high performance test on the domestic ship hydrodynamics numerical software is carried out. Selecting a typical Knock Nevis KCS model with a bulbous bow, through the parallel solver of the software, the wave-making problem of a real ship is simulated, in which the wave shape near the actual ship hull is basically consistent with that of the real ship. The successful test of a typical application scenario of the domestic …

An Efficient Tracker Via Multi-Feature Adaptive Correlation Filter, Sixian Zhang, Yi Yang, Meng Zhang, Pengbo Mi

Journal of System Simulation

Abstract: Aiming at the low tracking effect of the correlation filters tracker based on manual features in challenging scenes of rapid deformation and background clutter, a new correlation filter tracker based on Staple tracker is proposed. An appearance model based on HOG features and color-naming features is built to enhance the robustness to the challenging scenes of rapid deformation and background clutter. A self-adjust evaluation function is designed to merge the two kinds of feature information and a more discriminative feature is obtained. The novel online update strategies to reduce the training over-fitting and model drift for different features are …

Day Ahead Thermal-Photovoltaic Economic Dispatch Considering Uncertainty Of Photovoltaic Power Generation, Xinghua Liu, Chen Geng, Shenghan Xie, Jiaqiang Tian, Hui Cao

Journal of System Simulation

Abstract: Aiming at the uncertainty and randomness of photovoltaic power generation affected by weather factors, a mathematical model of day ahead thermal-photovoltaic economic dispatch considering seasonal weather factors is established. The mathematical model takes the operation cost of thermal power units, the cost of photovoltaic power generation, the cost of spinning reserve and the forecast error cost of photovoltaic power generation affected by weather factors as the economic objective function, and the sulfur dioxide emission of thermal power units as the environmental objective function. In order to improve the accuracy of photovoltaic output prediction, the long short term memory neural …

Scheduling Optimization And Comparative Analysis Of Twin 40 Feet Yard Crane Based On Saga, Meng Yu, Zhenli Xu, Tianjiao Tan

Journal of System Simulation

Abstract: Based on the operating characteristics of twin 40 ft yard crane, the scheduling models of the single-container yard crane, twin 40 ft yard crane with single-lift structure and twin 40 ft yard crane with twin-lift structure in the mixed container area are established respectively to minimize the operating time. simulate anneal genetic algorithm(SAGA) hybrid algorithm is used in the yard crane scheduling model to optimize the yard crane equipment configuration and scheduling strategy, shorten the average loading and unloading time, and improve the operation efficiency of the automatic terminal. By comparing the operation efficiency of three kinds of cranes …

Identification Of Switching Operation Based On Lstm And Moe, Xiaoqing Zhang, Wanfang Xiao, Yingjie Guo, Bowen Liu, Xuesen Han, Jingwei Ma, Gao Gao, He Huang, Shihong Xia

Journal of System Simulation

Abstract: Aiming at the individual differences of different personnel in the same operation and differences of the same person in the same operation at different times, a switching operation recognition model(MoE-LSTM) based on Mixture of experts model (MOE) and long short-term memory network(LSTM) is proposed. Based on MoE, LSTM is integrated to learn the feature distribution of different sources data. The acceleration data is collected to build the switching operation dataset and the action sequence is segmented and aligned based on sliding window. The action sequence is input to MoE-LSTM, and the temporal dependencies of different actions are independently learned …

Contents, Jaka Fajar Fatriansyah

Journal of Materials Exploration and Findings

No abstract provided.

Preface Of Volume 1 Issue 1 On Journal Of Materials Exploration And Findings (Jmef), Jaka Fajar Fatriansyah

Journal of Materials Exploration and Findings

No abstract provided.

The Optimization Of Failure Risk Estimation On The Uniform Corrosion Rate With A Non-Linear Function, Fernanda Hartoyo, Jaka Fajar Fatriansyah, Imam Abdillah Mas'ud, Farhan Rama Digita, Hanna Ovelia, D. Rizal Asral

Journal of Materials Exploration and Findings

Failures in the oil and gas pipeline system are conditions that must be avoided and anticipated because the losses due to the failures can occur at a very high level. Internal corrosion is one of the significant causes of the failures in pipeline systems. In addition, this type of corrosion is due to the high content of carbon dioxide and other corrosive substances in crude oil and natural gas. Therefore, an optimal inspection scheduling system is required to prevent the possibility of pipeline failures due to corrosion and to avoid any overspending on the budget due to excessive inspection scheduling. …

Assessing Readiness For Implementation Of Prognostics And Health Management In Small And Medium Enterprises, Sara C. Fuller

Theses and Dissertations

Prognostics and Health Management (PHM) refers to using robust sensing, monitoring, and control to detect, assess, and track system health degradation and failure modes, allowing for enhanced management and operational decisions. The need for PHM within a manufacturing facility has increased due to a variety of reasons, such as the increasing complexity of manufacturing equipment.

A lack of readiness for digital implementations is linked to failure. The literature highlights certain barriers and enablers that can signal whether a technology implementation will be successful, such as management and maintenance employees’ desire to change the existing process, an understanding and willingness to …

A Biomechanical Approach To Prevent Falls In Ergonomic Settings, Sachini Kodithuwakku Arachchige

Theses and Dissertations

Introduction: Fall-related injuries are exceptionally prevalent in occupational settings. While endangering the workers’ health, falls cause poor productivity and increased economic burden in the workplace. Hence, identifying these threats and training workers to achieve proper postural control is crucial. Purpose: Study 1: To investigate the ankle joint kinematics in unexpected and expected trip responses during single-tasking (ST), dual-tasking (DT), and triple-tasking (TT), before and after a physically fatiguing exercise. Study 2: To investigate the impact of virtual heights, DT, and training on static postural stability and cognitive processing. Methods: Study 1: Twenty collegiate volunteers (10 males and females, one left …

Bayesian Network Development For Depots Location Selection With Biomass Supply System Excellence, Alaa Ashraf Abulhamail

Theses and Dissertations

The renewable energy of the wood pellet market has taken great attention over the last few periods. However, the returns from the pellet business depend largely on how well the quality of biomass. The objective is to economically harvest pellets matching pellet standards set forward by the U.S. markets. The single-mindedness of this study is to develop a Bayesian network model to ensure a high-quality flow through the supply chain of the pallet industry in the top ten counties in Mississippi state. Multiple critical decisions (harvesting, storage, transportation, and quality control) of a biomass-to-pellet supply system could potentially affect the …

Bayesian Network Development And Validation For Siting Selection, Abdullah Hassan Battawi

Theses and Dissertations

In this study, increasing electricity demand requires considerable attention to increasing the diversity of power generation. Alternative energy can produce heating and power systems and thermal storage. Our objective and every organization’s objectives are to minimize its energy consumption cost under electricity demand uncertainty. In rural areas, heat and power availability and stability are also crucial. Combined heat and power have proven their effectiveness as a subsequent to Electricity. This paper identified four criteria and eleven sub-criteria to determine the most appropriate structure location for combined heat and power in the rural community. The Bayesian Network technology has been applied …

Developing Novel Optimization And Machine Learning Frameworks To Improve And Assess The Safety Of Workplaces, Amin Aghalari

Theses and Dissertations

This study proposes several decision-making tools utilizing optimization and machine learning frameworks to assess and improve the safety of the workplaces. The first chapter of this study presents a novel mathematical model to optimally locate a set of detectors to minimize the expected number of casualties in a given threat area. The problem is formulated as a nonlinear binary integer programming model and then solved as a linearized branch-and-bound algorithm. Several sensitivity analyses illustrate the model's robustness and draw key managerial insights. One of the prevailing threats in the last decades, Active Shooting (AS) violence, poses a serious threat to …

Optimization Of Drive Time And Competitiveness In Sports League Design, Zhuo Chen

Operations Research and Engineering Management Theses and Dissertations

Club sports, also known as recreational team sports, are prevalent in the metropolitan areas of United States nowadays. However, there is a key concern for organizers, which is how to reduce the time that players spend driving to and from matches while keeping league divisions competitive. We adopt a three-step approach to solve this problem. Initially, we analyze the drive time data between clubs’ locations to determine the geographic regions for the league. And then, clubs are assigned to divisions based on their rankings within in the league as well as their home facilities’ geographic regions. Finally, divisions are further …

Manufacturing & Service Systems, Robert S. Keyser

KSU Distinguished Course Repository

An analysis of decision making in the current production environment and the tools and optimization models needed for finding solutions to problems relating to production planning and scheduling, inventory, and warehouse design.

Lasso Based State Transition Modeling With Interactions In Adaptive Interdisciplinary Pain Management, Amith Viswanatha

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

The Eugene McDermott Center for Pain Management at the University of Texas Southwestern Medical Center has an interdisciplinary pain management program for chronic pain. This program treats patients with a holistic view of reducing chronic pain and improving their physical, mental, and social well-being through treatment interventions. The development of an adaptive treatment decision tool is main goal of the research project. This program is modeled as a two-stage adaptive treatment decision problem, with state transition models representing the transition of patient state, treatment, and outcome variables from stage 1 to stage 2. Interactions between the patient state and treatments …

A Hybrid Systems Model For Emergency Department Boarding Management, Eniola Oluwasola Suley

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

The purpose of this research is to examine methods for minimizing the influence of boarding on emergency department (ED) crowding outcomes. To accomplish this purpose, this research uses a hybrid systems model framework by combining agent-based simulation, predictive and optimization models to improve ED outcomes such as length-of-stay and left-without-being-seen rates. For the research, different types of simulation models were examined (discrete event and agent-based/discrete event combination) to identify the most parsimonious for studying ED boarding. Predictive models using simulation output were developed to understand the factors that influence future boarding levels as well as generate predictions. Research has previously …

Design And Operations Of A New Facility In A Next Generation Logistic System Based On Horizontal Collaboration, Dilhani Marasinghe

All Dissertations

The growing amount of freight combined with systemic inefficiencies are stressing current logistic systems. Including horizontal collaboration in the future could provide significant help but this strategy will require several new types of facilities. The most flexible type of horizontal collaboration, however, required freight routing decisions to be made dynamically, in real time, and based on last minute information. This research explores one new facility type operating in this environment that handles a high throughput of pallets or pallet-like containers. A key design feature is how much storage these facilities should have to better coordinate outbound loads. The approach taken …

Park Equity Modeling: A Case Study Of Asheville, North Carolina, Anisa Young

All Theses

Parks and greenspaces are publicly available entities that serve the vital purpose of promoting multiple aspects of human welfare. Unfortunately, the existence of park disparities is commonplace within the park setting. Specifically, marginalized individuals encounter limited park access, insufficient amenity provision, and poor maintenance. To remedy these disparities, we propose a process in which we select candidate park facilities and utilize facility location models to determine the optimal primary parks from both existing and candidate sites.

We note that platforms currently exist to identify the geographical areas where residents lack sufficient access to parks. However, these platforms do not yet …

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson

Graduate Theses and Dissertations

This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …

Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang

Information Technology & Decision Sciences Faculty Publications

(First paragraph) Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives. In this Special Issue (SI), SM refers to a system paradigm where digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the internet to expand system capabilities, (3) supporting data-driven decision making at all domains and levels of businesses, or (4) reconfiguring systems to adapt changes and uncertainties in dynamic environments. …

Ensemble Tree-Based Machine Learning For Imaging Data, Reza Iranzad

Graduate Theses and Dissertations

In particular medical imaging data, such as positron emission tomography (PET), computed tomography (CT), and fluorescence intravital microscopy (IVM), have become prevalent for use in a wide variety of applications, from diagnostic purposes, tracking diseases' progress, and monitoring the effectiveness of treatments to decision-making processes. The detailed information generated by medical imaging has enabled physicians to provide more comprehensive care. Although numerous machine learning algorithms, especially those used for imaging data, have been developed, dealing with unique structures in imaging data remained a big challenge. In this dissertation, we are proposing novel statistical tree-based methods with more efficient and more …

Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey

Graduate Theses and Dissertations

Deep learning - the use of large neural networks to perform machine learning - has transformed the world. As the capabilities of deep models continue to grow, deep learning is becoming an increasingly valuable and practical tool for industrial engineering. With its wide applicability, deep learning can be turned to many industrial engineering tasks, including optimization, heuristic search, and functional approximation. In this dissertation, the major concepts and paradigms of deep learning are reviewed, and three industrial engineering projects applying these methods are described. The first applies a deep convolutional network to the task of absolute aerial geolocalization - the …