Operational Research Commons^™

การจัดเส้นทางการเดินรถที่มีหลายจุดกระจายสินค้าโดยพิจารณารอบเวลาการวางแผน, วัสพล ตรีธนวัต

Chulalongkorn University Theses and Dissertations (Chula ETD)

การศึกษานี้มุ่งเน้นการแก้ปัญหาการจัดส่งอาหารแบบพลวัต โดยที่คำสั่งซื้อเข้ามาในระบบแบบพลวัตและต้องจัดส่งถึงลูกค้าภายในกรอบเวลาที่กำหนด โดยใช้ยานพาหนะที่มีความจุจำกัดสำหรับการจัดส่ง เป้าหมายหลักคือการลดระยะทางในการขนส่งทั้งหมดให้น้อยที่สุด พร้อมกับตอบสนองความต้องการของลูกค้าได้ทันเวลา ผู้เขียนได้นำเสนอวิธีการแก้ปัญหาที่ประกอบด้วย 2 ขั้นตอนหลัก คือ 1. การจัดกลุ่มคำสั่งซื้อ คือทำการจัดกลุ่มคำสั่งซื้อตามเวลาที่คำสั่งซื้อเข้ามาและกรอบเวลาการจัดส่ง และ 2. การปรับเส้นทางสำหรับแต่ละกลุ่มคำสั่งซื้อ จะทำการคำนวณเส้นทางการจัดส่งที่เหมาะสมที่สุด โดยใช้โมเดลปัญหาการจัดเส้นทางการขนส่งแบบมีกรอบเวลา วิธีการนี้ได้รับการประเมินโดยการทดลอง ซึ่งแสดงให้เห็นว่ากรอบเวลาการตัดสินใจ หรือช่วงเวลาที่ใช้ในการจัดกลุ่มคำสั่งซื้อ มีผลกระทบต่อผลลัพธ์ หากกรอบเวลาการตัดสินใจแคบลง จะต้องใช้จำนวนยานพาหนะที่มากขึ้นเมื่อเทียบกับกรอบเวลาที่กว้างขึ้น แต่จะช่วยลดเวลาเฉลี่ยที่ลูกค้าต้องรอได้ ในขณะที่กรอบเวลาที่กว้างขึ้น ช่วยให้สามารถรวมคำสั่งซื้อหลายรายการไว้ในเส้นทางการจัดส่งเดียวกันได้มากขึ้น ซึ่งอาจลดต้นทุนระยะทางการเดินทางลงได้ อย่างไรก็ตาม หากกรอบเวลากว้างเกินไป อาจส่งผลให้ระยะทางเพิ่มขึ้น เนื่องจากช่วงเวลาระหว่างการตัดสินใจและเวลาจัดส่งที่กำหนดไว้น้อยเกินไป จนทำให้เกิดการเพิ่มรอบขนส่งอาหาร

การจัดสมดุลสายการประกอบแบบขนานหลายวัตถุประสงค์ที่ทำงานโดยพนักงานหลายทักษะและหุ่นยนต์, ธนภัทร์ จิตรศรีศักดา

Chulalongkorn University Theses and Dissertations (Chula ETD)

การจัดสมดุลสายการประกอบแบบขนานที่ประกอบด้วยพนักงานปกติ ผู้พิการ ผู้สูงอายุ และหุ่นยนต์ Cobot โดยการพิจารณาทุกฟังก์ชันวัตถุประสงค์ไปพร้อมๆกันจัดเป็นปัญหาเอ็นพีแบบยาก (NP-Hard) ที่มีความยุ่งยากและซับซ้อนของปัญหาดังนั้น จึงต้องพิจารณาใช้วิธีการแก้ปัญหาแบบฮิวริสติก (Heuristic) และเมตาฮิวริสติก (Meta-Heuristic) มาช่วยในการแก้ปัญหา งานวิจัยนี้ได้มีการนำเสนอพนักงานหลายทักษะซึ่งจะมีข้อจำกัดแตกต่างกันไป โดยจะมีพนักงานปกติ พนักงานผู้พิการ และพนักงานผู้สูงอายุ เพื่อจะดูว่าการใช้พนักงานประเภทต่างๆจะมีผลกระทบต่อประสิทธิภาพของสายการประกอบอย่างไร งานวิจัยนี้ใช้วิธีเชิงพันธุกรรมแบบการจัดลำดับที่ไม่ถูกครอบงำในการพัฒนาหาคำตอบของฟังก์ชันวัตถุประสงค์ ซึ่งเป็นการจำลองสายการประกอบโดยฟังก์ชันวัตถุประสงค์ประกอบด้วย 1) ประสิทธิภาพของสายการประกอบมากที่สุด 2) พลังงานไฟฟ้าที่หุ่นยนต์หรือ Cobot ใช้ในการทำงานน้อยที่สุด และ 3) ความแตกต่างด้านการใช้พลังงานของพนักกงงานน้อยที่สุด ผลการศึกษาแสดงให้เห็นว่าการใช้ Cobot สามารถลดภาระงานของพนักงาน โดยเฉพาะงานที่ต้องการความแม่นยำหรือทักษะเฉพาะทาง และเพิ่มความยืดหยุ่นให้กับสายการประกอบ นอกจากนี้ การกระจายภาระงานระหว่าง Cobot และพนักงานจะช่วยลดการใช้พลังงานเฉลี่ยต่อ Cobot และทำให้การใช้งานพลังงานของพนักงานมีความสมดุลมากขึ้น ส่งผลให้ความแปรปรวนของภาระงานลดลง และการจัดสมดุลพลังงานในสายการประกอบมีความสมดุลมากขึ้น กล่าวโดยสรุปก็คือ Cobot มีบทบาทสำคัญในการเพิ่มประสิทธิภาพและความยืดหยุ่นของสายการประกอบ พร้อมช่วยลดข้อจำกัดด้านแรงงานและพลังงานได้อย่างชัดเจน

Virtual Reality Of Labless Machining For Next Industrial Training, Ravee Bunduwongse

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study aims to utilize Virtual Reality (VR) technology to develop an industrial training application with content focusing on Machining operation using lathe machine. The focus of the study is to present the content being taught in manufacturing laboratory classes about lathe machining operations in the virtual world. Development tools include Unity game engine and 3D modeling using Blender. Machining operations demonstrated within this application includes turning, facing, chamfering, grooving, internal and external threading. With 17 out of 18 operations represented in accordance to the actual teaching material, with only external threading deviating from applying threading using the lathe machine …

Virtual Reality Of Labless Welding For Next Industrial Training, Suphakit Anonglekha

Chulalongkorn University Theses and Dissertations (Chula ETD)

This research introduces an innovative Virtual Reality (VR) application designed to educate users on Welding operations. Its main goals include creating a realistic and immersive learning environment that is also safe. The development process involved the integration of multiple technologies, leveraging the Unity engine and 3D sculpting, all based on extensive research. With all of the type of weld works found in the welding laboratory represented, except the workpiece and electrode material, the VR application accuracy rating is calculated to 94%. The study's significance lies in its contribution to virtual education, especially in fields that require hands-on experience. The VR …

Milk Collection Problem: Integrating The Traveling Salesman And Set Covering Problem - A Case Study In West Virginia, Usa, Md Rabiul Hasan

Graduate Theses, Dissertations, and Problem Reports (ETD)

Route determination for perishable products is complex due to its unique characteristics, such as limited shelf-life regulatory requirements, or possibility of getting damaged. This research investigates a novel problem of collecting raw milk from a rural network of dairy farms. The research problem is grounded in a real scenario of milk collection in West Virginia, USA. The milk in this scenario is produced by small farms incapable of realizing transportation economies of density out in mostly rural areas throughout the state. Maximum coverage area and milk processing overhead costs are used to identify suitable locations for intermediate milk collection centers …

Essays In Robust Optimization With Applications To Finance And Renewable Energy, Hao Jiang

Operations Research and Engineering Management Theses and Dissertations

Real-world optimization problems are often sensitive to uncertainties caused by estimation errors, forecasting inaccuracy, and imprecise data information. These uncertainties bring significant challenges to decision-making in many areas. Robust optimization (RO) is a tool for addressing the challenges of parameter uncertainty. In this dissertation, we focus on the studies of RO on two problems. (1) In the study of finance, we proposed a tractable RO model for a Mean-Variance portfolio selection problem. We consider Markowitz's Mean-Variance Optimization when stock returns are modeled using Sharpe's single-index framework, but the model coefficients Alpha and Beta, are not precisely known. This study assumes …

Reliability Modeling And Improvement Of Critical Infrastructures: Theory, Simulation, And Computational Methods, José Carlos Hernández Azucena

Graduate Theses and Dissertations

This dissertation presents a framework for developing data-driven tools to model and improve the performance of Interconnected Critical Infrastructures (ICIs) in multiple contexts. The importance of ICIs for daily human activities and the large volumes of data in continuous generation in modern industries grant relevance to research efforts in this direction. Chapter 2 focuses on the impact of disruptions in Multimodal Transportation Networks, which I explored from an application perspective. The outlined research directions propose exploring the combination of simulation for decision-making with data-driven optimization paradigms to create tools that may provide stakeholders with optimal policies for a wide array …

Task Optimization Utilizing Digital Transformation Concepts - Automation Project Execution Via Agile Methodology, Anthony Steven Maiello

Theses and Dissertations

Task Optimization via the use of automated process improvements is becoming more widespread as more industries lean into the concepts surrounding digital transformation. This shift also necessitates a complementary adaptation in project management methodologies to support the rapid and ever-changing environment, requirements, and innovations. This thesis examines the effectiveness of Agile methodology in managing digital automation projects, with a specific focus placed on process improvements with systems engineering. It accomplished this by contrasting the original model, designed and derived utilizing traditional project management techniques, with the proposed model which is a direct result of the application of Agile project practices. …

Federated Active Learning For Network Intrusion Detection, Matthew D. R. Sauer

Theses and Dissertations

This thesis addresses challenges with detecting attacks on computer networks within a Federated Learning (FL) framework, when labeled instances are few. We explore the integration of active learning (AL) and semi-supervised learning (SSL). AL efficiently uses data that would otherwise be wasted or require substantial time for labeling. SSL provides capacity to train models that have a limited amount of labeled data, by utilizing additional unlabeled data that is available. We show how FL combined with AL or SSL can realize a detection system that adapts and trains quickly to new networks, reducing the total amount of data labeling needed. …

Evaluating The Chief Of Staff Of The Air Force 2016 Initiative To Revitalize The Squadron: A Thematic Content Analysis Of Appreciative Inquiry Mechanisms, John M. Huntz

Theses and Dissertations

A thorough thematic analysis and literature review were undertaken to understand better the integration of AI mechanisms within the Revitalize the Squadron initiative. To facilitate the initiative's implementation, the aim is to provide commanders with practical instances, dimensions, findings, and results. Throughout the coding process, instances of AI’s mechanisms were discovered in the literature. The link between PE and HQR boosted the overall vitality within the squadron, where vitality was determined to be the goal. AI, as a whole, was not found in the literature, but the analysis determined that the Revitalize the Squadron initiative was “Appreciative” in nature.

Network Vulnerability Identification For The Material Routing Problem, Carson G. Long

Theses and Dissertations

This dissertation considers the importance of identifying spatiotemporal vulnerabilities in ground distribution networks and uses operations research methods to formulate models that allow military logistic planners to implement prevention and mitigation measures regarding the routing of personnel, equipment, and supplies in contested Areas of Responsibility (AOR). For optimization models relating to identifying spatiotemporal network vulnerabilities in distribution networks, this work leverages game theory, mixed-integer programming, multi-objective optimization, and metaheuristics to inform mitigation measures for shipment routing. This research has three related components: the first component develops a multi-objective mathematical program to identify spatiotemporal vulnerabilities via myopic heuristic identification, in combination …

Improving Deep Reinforcement Learning Methodology For Autonomous Defense And Escort Of Military High-Value Assets, Joseph Liles Iv

Theses and Dissertations

This dissertation explores the application of machine learning to the control of autonomous unmanned combat aerial vehicles (AUCAVs). In particular, this research applies deep reinforcement learning methodologies to a defensive air combat scenario wherein a fleet of AUCAVs protects a military high-value asset (HVA). A collection of air battle management scenarios along with an original simulation environment and a set of designed computational experiments support the approximation of high-quality decision policies by employing Markov decision processes, approximate dynamic programming algorithms, and deep neural networks for value function approximation.

Test Problem Generation And Metaheuristic Selection For The Multidemand Multidimensional Knapsack Problem, Matthew E. Scherer

Theses and Dissertations

This work focuses on instance generation methods for the multi-demand multidimensional knapsack problem (MDMKP). Specifically, instance space analysis (ISA) is used to characterize the landscape of existing instances and validate the novelty of new instances generated with a novel problem generation method, the primal problem instance generator (PPIG). The instance generator is capable of producing feasible, diverse, and challenging instances by directly controlling the problem features. PPIG contributes to the previous collections of instances and is validated through instance space analysis. The research presents an in-depth empirical evaluation of existing solution procedures for the MDMKP. The portfolio of metaheuristics examined …

Optimal Sequencing And Scheduling Algorithm For Traffic Flows Based On Extracted Control Actions Near The Airport, Sharmistha Chakrabarti

Electronic Theses and Dissertations, 2020-2023

This dissertation seeks to design an optimization algorithm, based on naturalistic flight data, with emphasis on safety to perform a benefits' analysis when sequencing and scheduling aircraft at the runway. The viability of creating a decision-support tool to aid air traffic controllers in sequencing and optimizing airport operations is evaluated through the benefits' analysis. Air traffic control is a complex and critical system that ensures the safe and efficient movement of aircraft within the airspace. This is particularly true in the immediate vicinity of an airport. Unlike in en-route or terminal area airspace where aircraft usually traverse well established routes …

Health-Care And Supportive Services In General Population Disaster Shelters, Ashlea Bennett Milburn, Charleen C. Mcneill, Lauren Clay, Janice Springer, Mary Casey-Lockyer

Industrial Engineering Faculty Publications and Presentations

Objectives:

The Communication (C), Maintaining Health (M), Independence (I), Services, Support and Self-Determination (S), and Transportation (T) is a framework (C-MIST) for identifying functional needs in an emergency response. A C-MIST documentation tool provides shelter staff with a list of potential client needs and actions to address them. This retrospective review describes the needs and actions indicated on completed C-MIST documentation tools (ie, records) within domestic general population shelters following Hurricane Florence in 2018.

Methods:

A convenience sample of 1209 records completed by shelter disaster health services personnel was provided by the American Red Cross. The records correspond to client …

Visibility Based Hospital Inpatient Unit Design., Uttam Karki

Electronic Theses and Dissertations

Patient fall is one of the adverse events in an inpatient unit of a hospital that can lead to disability and/or mortality. Healthcare literature suggests that increased visibility of patients by unit nurses is essential to improve patient monitoring and, in turn, reduce falls. However, such research has been descriptive in nature and does not provide an understanding of the characteristics of an optimal inpatient unit layout from a visibility-standpoint. This dissertation fills significant voids in this domain and adds much-needed realism to develop insights that hospital decision-makers can use to design their inpatient unit layout. Our first contribution (Chapter …

Modeling And Solution Methodologies For Mixed-Model Sequencing In Automobile Industry, Ibrahim Ozan Yilmazlar

All Dissertations

The global competitive environment leads companies to consider how to produce high-quality products at a lower cost. Mixed-model assembly lines are often designed such that average station work satisfies the time allocated to each station, but some models with work-intensive options require more than the allocated time. Sequencing varying models in a mixed-model assembly line, mixed-model sequencing (MMS), is a short-term decision problem that has the objective of preventing line stoppage resulting from a station work overload. Accordingly, a good allocation of models is necessary to avoid work overload. The car sequencing problem (CSP) is a specific version of the …

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

Domain Restriction Zones: An Evolution Of The Military Exclusion Zone, Cole M. Mooty, Robert A. Bettinger, Mark G. Reith

Faculty Publications

Since the early part of the twenty-first century, US adversaries have expanded their military capabilities within and their access to new warfighting domains. When faced with the growth of adversaries’ asymmetric capabilities, the means, tactics, and strategies previously used by the US military lose their proportional effectiveness. To avoid such degradation of capability, the operational concept of the military exclusion zone (MEZ) should be revised to suit the modern battlespace while also addressing the shifts in national policy that encourage diplomacy over military force. The concept and development of domain restriction zones (DRZs) increase the relevancy of traditional MEZs in …

A Case For An Independent Cyber Force, Ian C. Heffron, Mark Reith, James W. Dean

Faculty Publications

Although cyberspace is considered the newest warfighting domain, military analysts and scholars have opined the United States remains woefully behind its peers in cyberspace and have called for the creation of a separate cyber service component. Yet a cohesive and robust discussion on this topic has yet to emerge. This article proposes a general framework that builds on the Joint doctrine, organization, training, materiel, leadership and education, personnel, facilities, and policy (DOTMLPF-P) analysis to address questions of sufficiency and necessity. Such analysis reveals DoD cyber operations do not maximize the United States’ ability to fight a cyber war, especially when …

Resources Based Planning Framework For Infrastructure Maintenance And Rehabilitation Projects, Heba Gad

Theses and Dissertations

Infrastructure maintenance and rehabilitation projects involve activities scattered over a large geographical area (e.g., scattered road segments maintenance, telecom towers maintenance program, etc.). Planning such projects require a resource-based approach that accounts for the implications of resource mobility between activities’ locations in terms of time & cost. Existing scheduling techniques fall short of addressing the unique challenges of the scattered nature of these projects in combination with organization's limited resources availability. To address this need, this research presents a resources-based planning framework for infrastructure maintenance and rehabilitation scattered projects with the objective of enhancing resources utilization achieving time and cost …

An Lp-Based Characterization Of Solvable Qap Instances With Chess-Board And Graded Structures, Lucas Waddell, Jerry Phillips, Tianzhu Liu, Swarup Dhar

Faculty Journal Articles

The quadratic assignment problem (QAP) is perhaps the most widely studied nonlinear combinatorial optimization problem. It has many applications in various fields, yet has proven to be extremely difficult to solve. This difficulty has motivated researchers to identify special objective function structures that permit an optimal solution to be found efficiently. Previous work has shown that certain such structures can be explained in terms of a mixed 0-1 linear reformulation of the QAP known as the level-1 reformulation-linearization-technique (RLT) form. Specifically, the objective function structures were shown to ensure that a binary optimal extreme point solution exists to the continuous …

Data-Driven Platform And Digital Operations, Bing Bai

Olin Business School Graduate Student Theses and Dissertations

The objective of this dissertation is to study the emerging operations issues on data-driven platforms and digital operations. With the increasing availability of data and the development of information technologies, platforms process a large amount of data in order to efficiently make daily operational decisions. Understanding human behaviors and the human-algorithm connection is instrumental to the success of this process. In my research, I implement field experiments and use structural models to study in-warehouse worker behavior and out-of-warehouse customer behavior in the last mile of logistics.

In Chapter 1, “The Impacts of Algorithmic Work Assignment on Fairness Perceptions and Productivity: …

Lead Distribution Modeling For Supply Chains With A Large Number Of Items, Wesley Tate

Industrial Engineering Undergraduate Honors Theses

Adding randomness into a simulation model allows for a better understanding of the variation that can occur in a real-life setting. This paper documents the methodology used to recommend a set of distribution models to cover administrative and production lead times for the simulation program involving hundreds of thousands of items. The problem of distribution fitting for large datasets is addressed, with histograms, Q-Q, and P-P plots being used to verify models in addition to goodness-of-fit test statistics. Variable level reduction using frequency and distribution matching approaches are outlined followed by the use of random forest modeling to identify key …

Optimizing Wedding Venue Selection Process Using Integer Programming, Luis Rodriguez

Theses/Capstones/Creative Projects

Choosing the right wedding venue can be extremely difficult for the unsuspecting engaged couple. There is a myriad of variables that must be taken into account prior to the illustrious wedding date; these variables include the option for a reception, the location, and food requirements, to name a few. Consequently, the typical couple seems to spend multiple months researching and visiting many wedding spaces. However, even though months go into planning, it still is not a guarantee that all variables are accounted for. Furthermore, without a wedding planner, these couples may second-guess their chosen site due to seemingly arduous issues …

Electric Vehicle Routing Problem – Models And Algorithms, Hesamoddin Tahami

Engineering Management & Systems Engineering Theses & Dissertations

The transportation sector is a major greenhouse gas emitter that is heavily regulated to reduce its dependence on oil. These regulations along with the growing customer awareness of global warming have led to the investigation of new transportation problems that consider using eco-friendly vehicle fleets. Promising alternatives to traditional fleets include alternative fuel vehicles (AFVs) and electric vehicles (EVs). These twenty-first-century vehicles offer an appealing advantage of consistently reducing their environmental impact, but due to the current technology, they exhibit bothersome limitations. The short driving range along with limited charging infrastructure may consequently cause issues related to range anxiety, i.e., …

Efficient Routing For Disaster Scenarios In Uncertain Networks: A Computational Study Of Adaptive Algorithms For The Stochastic Canadian Traveler Problem With Multiple Agents And Destinations, Neel Chanchad

Graduate Theses and Dissertations

The primary objective of this research is to develop adaptive online algorithms for solving the Canadian Traveler Problem (CTP), which is a well-studied problem in the literature that has important applications in disaster scenarios. To this end, we propose two novel approaches, namely Maximum Likely Node (MLN) and Maximum Likely Path (MLP), to address the single-agent single-destination variant of the CTP. Our computational experiments demonstrate that the MLN and MLP algorithms together achieve new best-known solutions for 10,715 instances. In the context of disaster scenarios, the CTP can be extended to the multiple-agent multiple-destination variant, which we refer to as …

A Comparison Of Nonverbal And Paraverbal Behaviors In Simulated And Virtual Patient Encounters, Sarah Powers, Mark W. Scerbo, Matthew Pacailler, Macy Kisiel, Baillie Hirst, Ginger S. Watson, Lauren Hamel, Fred Kron

Modeling, Simulation and Visualization Student Capstone Conference

The present study assessed whether trainees display similar nonverbal and paraverbal behaviors when interacting with a simulated (SP) and virtual patient (VP). Sixty second slices of time following four interactions were rated for the presence and frequency of three nonverbal and paraverbal behaviors. Results revealed that students exhibited fewer behaviors in the VP interaction, possibly due to differences social inhibition or fidelity between the two formats.

Urban Public Transportation Planning With Endogenous Passenger Demand, Yifei Sun

Dartmouth College Ph.D Dissertations

An effective and efficient public transportation system is crucial to people's mobility, economic production, and social activities. The Operations Research community has been studying transit system optimization for the past decades. With disruptions from the private sector, especially the parking operators, ride-sharing platforms, and micro-mobility services, new challenges and opportunities have emerged. This thesis contributes to investigating the interaction of the public transportation systems with significant private sector players considering endogenous passenger choice. To be more specific, this thesis aims to optimize public transportation systems considering the interaction with parking operators, competition and collaboration from ride-sharing platforms and micro-mobility platforms. …