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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Characterizing Linearizable Qaps By The Level-1 Reformulation-Linearization Technique, Lucas Waddell, Warren Adams Feb 2024

Characterizing Linearizable Qaps By The Level-1 Reformulation-Linearization Technique, Lucas Waddell, Warren Adams

Faculty Journal Articles

The quadratic assignment problem (QAP) is an extremely challenging NP-hard combinatorial optimization program. Due to its difficulty, a research emphasis has been to identify special cases that are polynomially solvable. Included within this emphasis are instances which are linearizable; that is, which can be rewritten as a linear assignment problem having the property that the objective function value is preserved at all feasible solutions. Various known sufficient conditions for identifying linearizable instances have been explained in terms of the continuous relaxation of a weakened version of the level-1 reformulation-linearization-technique (RLT) form that does not enforce nonnegativity on a subset …


An Algorithm Based On Priority Rules For Solving A Multi-Drone Routing Problem In Hazardous Waste Collection, Youssef Harrath Dr., Jihene Kaabi Dr. Jan 2024

An Algorithm Based On Priority Rules For Solving A Multi-Drone Routing Problem In Hazardous Waste Collection, Youssef Harrath Dr., Jihene Kaabi Dr.

Research & Publications

This research investigates the problem of assigning pre-scheduled trips to multiple drones to collect hazardous waste from different sites in the minimum time. Each drone is subject to essential restrictions: maximum flying capacity and recharge operation. The goal is to assign the trips to the drones so that the waste is collected in the minimum time. This is done if the total flying time is equally distributed among the drones. An algorithm was developed to solve the problem. The algorithm is based on two main ideas: sort the trips according to a given priority rule and assign the current trip …


Optimal Algorithm For Managing On-Campus Student Transportation, Youssef Harrath Dr. Jan 2024

Optimal Algorithm For Managing On-Campus Student Transportation, Youssef Harrath Dr.

Research & Publications

This study analyzed the transportation issues at the University of Bahrain Sakhir campus, where a bus system with an unorganized and fixed number of buses allocated each semester was in place. Data was collected through a survey, on-site observations, and student schedules to estimate the number of buses needed. The study was limited to students who require to move between buildings for academic purposes and not those who choose to ride buses for other reasons. An algorithm was designed to calculate the optimal number of buses for each time slot, and for each day. This solution could improve transportation efficiency, …


Domain Restriction Zones: An Evolution Of The Military Exclusion Zone, Cole M. Mooty, Robert A. Bettinger, Mark G. Reith Jul 2023

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 …


An Lp-Based Characterization Of Solvable Qap Instances With Chess-Board And Graded Structures, Lucas Waddell, Jerry Phillips, Tianzhu Liu, Swarup Dhar May 2023

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 …


Ant Colony-Based Approach For Solving An Unmanned Aerial Vehicle Routing Problem, Youssef Harrath Dr., Jihene Kaabi Dr. Jan 2023

Ant Colony-Based Approach For Solving An Unmanned Aerial Vehicle Routing Problem, Youssef Harrath Dr., Jihene Kaabi Dr.

Research & Publications

Waste management issues are affecting the economic and environmental aspects of modern societies. Thus, growing the interest of academic and industrial research and development in optimizing the process of waste management. As these issues greatly impact human health and environmental aspects and impose a threat, hazardous waste management requires even much more attention. The problem studied in this research is a variant of the vehicle routing problem using an unmanned aerial vehicle (UAV). The focus of this research is on planning the routes for waste collection and disposal using a UAV. The aim is to collect all the waste as …


Recall Distortion In Neural Network Pruning And The Undecayed Pruning Algorithm, Aidan Good, Jiaqi Lin, Hannah Sieg, Mikey Ferguson, Xin Yu, Shandian Zhe, Jerzy Wieczorek, Thiago Serra Nov 2022

Recall Distortion In Neural Network Pruning And The Undecayed Pruning Algorithm, Aidan Good, Jiaqi Lin, Hannah Sieg, Mikey Ferguson, Xin Yu, Shandian Zhe, Jerzy Wieczorek, Thiago Serra

Faculty Conference Papers and Presentations

Pruning techniques have been successfully used in neural networks to trade accuracy for sparsity. However, the impact of network pruning is not uniform: prior work has shown that the recall for underrepresented classes in a dataset may be more negatively affected. In this work, we study such relative distortions in recall by hypothesizing an intensification effect that is inherent to the model. Namely, that pruning makes recall relatively worse for a class with recall below accuracy and, conversely, that it makes recall relatively better for a class with recall above accuracy. In addition, we propose a new pruning algorithm aimed …


Using Strategic Options Development And Analysis (Soda) To Understand The Simulation Accessibility Problem, Andrew J. Collins, Ying Thaviphoke, Antuela A. Tako Nov 2022

Using Strategic Options Development And Analysis (Soda) To Understand The Simulation Accessibility Problem, Andrew J. Collins, Ying Thaviphoke, Antuela A. Tako

Engineering Management & Systems Engineering Faculty Publications

Simulation modelling is applied to a wide range of problems, including defense and healthcare. However, there is a concern within the simulation community that there is a limited use and implementation of simulation studies in practice. This suggests that despite its benefits, simulation may not be reaching its potential in making a real-world impact. The main reason for this could be that simulation tools are not widely accessible in industry. In this paper, we investigate the issues that affect simulation modelling accessibility through a workshop with simulation practitioners. We use Strategic Options Development and Analysis (SODA), a problem-structuring approach that …


Training Thinner And Deeper Neural Networks: Jumpstart Regularization, Carles Riera, Camilo Rey, Thiago Serra, Eloi Puertas, Oriol Pujol Jun 2022

Training Thinner And Deeper Neural Networks: Jumpstart Regularization, Carles Riera, Camilo Rey, Thiago Serra, Eloi Puertas, Oriol Pujol

Faculty Conference Papers and Presentations

Neural networks are more expressive when they have multiple layers. In turn, conventional training methods are only successful if the depth does not lead to numerical issues such as exploding or vanishing gradients, which occur less frequently when the layers are sufficiently wide. However, increasing width to attain greater depth entails the use of heavier computational resources and leads to overparameterized models. These subsequent issues have been partially addressed by model compression methods such as quantization and pruning, some of which relying on normalization-based regularization of the loss function to make the effect of most parameters negligible. In this work, …


An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms, Yanchao Liu Apr 2022

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

Industrial and Systems Engineering Faculty Research Publications

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


The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick Apr 2022

The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick

Senior Honors Theses

One of the most investigated topics in operations research is the Traveling Salesman Problem (TSP) and the algorithms that can be used to solve it. Despite its relatively simple formulation, its computational difficulty keeps it and potential solution methods at the forefront of current research. This paper defines and analyzes numerous proposed solutions to the TSP in order to facilitate understanding of the problem. Additionally, the efficiencies of different heuristics are studied and compared to the aforementioned algorithms’ accuracy, as a quick algorithm is often formulated at the expense of an exact solution.


Strengthening A Linear Reformulation Of The 0-1 Cubic Knapsack Problem Via Variable Reordering, Richard Forrester, Lucas Waddell Jan 2022

Strengthening A Linear Reformulation Of The 0-1 Cubic Knapsack Problem Via Variable Reordering, Richard Forrester, Lucas Waddell

Faculty Journal Articles

The 0-1 cubic knapsack problem (CKP), a generalization of the classical 0-1 quadratic knapsack problem, is an extremely challenging NP-hard combinatorial optimization problem. An effective exact solution strategy for the CKP is to reformulate the nonlinear problem into an equivalent linear form that can then be solved using a standard mixed-integer programming solver. We consider a classical linearization method and propose a variant of a more recent technique for linearizing 0-1 cubic programs applied to the CKP. Using a variable reordering strategy, we show how to improve the strength of the linear programming relaxation of our proposed reformulation, which ultimately …


Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk Jan 2022

Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk

VMASC Publications

Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about …


Human Ergonomic Simulation To Support The Design Of An Exoskeleton For Lashing/De-Lashing Operations Of Containers Cargo, Francesco Longo, Antonio Padovano, Vittorio Solina, Virginia D' Augusta, Stefan Venzl, Roberto Calbi, Michele Bartuni, Ornella Anastasi, Rafael Diaz Jan 2022

Human Ergonomic Simulation To Support The Design Of An Exoskeleton For Lashing/De-Lashing Operations Of Containers Cargo, Francesco Longo, Antonio Padovano, Vittorio Solina, Virginia D' Augusta, Stefan Venzl, Roberto Calbi, Michele Bartuni, Ornella Anastasi, Rafael Diaz

VMASC Publications

Lashing and de-lashing operations of containers cargo on board containerships are considered as quite strenuous activities in which operators are required to work continuously over a 6 or 8 hours shift with very limited break. This is mostly because containerships need to leave the port as soon as possible and containers loading and unloading operations must be executed with very high productivity (stay moored in a port is a totally unproductive time for a ship and a loss-making business for a shipping company). Operators performing lashing and de-lashing operations are subjected to intense ergonomic stress and uncomfortable working postures. To …


Exact Algorithms For Practical Instances Of The Railcar Loading Problem At Marine Container Terminals, Manwo Ng, Dung-Ying Lin Jan 2022

Exact Algorithms For Practical Instances Of The Railcar Loading Problem At Marine Container Terminals, Manwo Ng, Dung-Ying Lin

Information Technology & Decision Sciences Faculty Publications

With the growth in global trade and its environmental footprint, sustainable modes of freight movement are increasingly important in today’s globalized world. This study focuses on on-dock rail, where the rail terminal is located within the marine container terminal. On-dock rail has in recent years become an essential mode of transportation to move containers out of congested marine container terminals. This study contributes to the literature by presenting tailored exact solution algorithms for a recently proposed optimization model to optimize the loading of double-stack trains. In particular, a 3-stage solution framework is presented for the case when rail cars have …


Analysis Of The Effects Of Spatiotemporal Demand Data Aggregation Methods On Distance And Volume Errors, Zachary Hornberger, Bruce A. Cox, Raymond R. Hill Aug 2021

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 …


Preventing Transmission Of Covid 19 In Hvac Duct Systems: Implementations Of Hvac System Design Upgrade, Jacob S. Lopez, Adama Barro Jun 2021

Preventing Transmission Of Covid 19 In Hvac Duct Systems: Implementations Of Hvac System Design Upgrade, Jacob S. Lopez, Adama Barro

Publications and Research

The recent pandemic outbreak has triggered a global alarm to increase efforts on finding the best methods to mitigate contagious viral pathogens. This project is a continuation of our mission to study engineering guidelines needed to implement upgrades to HVAC Systems in order to deter airborne pathogens such as the covid-19 virus. In our previous projects we researched how covid-19 can possibly flow through the ambient air inside of restaurants, office spaces, and locomotive train cabins. As we continued our research, we were able to find some solutions that will be best used to deactivate and prevent the virus from …


Integration Of Blockchain Technology Into Supply Network For Resilient And Efficient Acquisition [Video], Adrian Gheorghe, Farinaz Sabz Ali Pour, Unal Tatar, Omer Faruk Keskin, Cornel Vintila, Laura Manciu May 2021

Integration Of Blockchain Technology Into Supply Network For Resilient And Efficient Acquisition [Video], Adrian Gheorghe, Farinaz Sabz Ali Pour, Unal Tatar, Omer Faruk Keskin, Cornel Vintila, Laura Manciu

Engineering Management & Systems Engineering Faculty Publications

In the modern acquisition, it is unrealistic to consider single entities as producing and delivering a product independently. Acquisitions usually take place through supply networks. Resiliency, efficiency, and effectiveness of supply networks directly contribute to the acquisition system's resiliency, efficiency, and effectiveness. All the involved firms form a part of a supply network essential to producing the product or service. The decision-makers have to look for new methodologies for supply chain management. Blockchain technology introduces new methods of decentralization and delegation of services, which can transform supply chains and result in a more resilient, efficient, and effective supply chain. This …


Heuristics For Capacity Allocation And Queue Assignment In Congested Service Systems With Stochastic Customer Demand And Immobile Servers, Adam Colley Apr 2021

Heuristics For Capacity Allocation And Queue Assignment In Congested Service Systems With Stochastic Customer Demand And Immobile Servers, Adam Colley

Operations Research and Engineering Management

We propose easy-to-implement heuristics for a problem referred to in the literature as the facility location problem with immobile servers, stochastic demand, and congestion, or the service system design problem. The problem is typically posed as one of allocating capacity to a set of M/M/1 queues to which customers with stochastic demand are assigned with the objective of minimizing a cost function composed of a fixed capacity-acquisition cost, a variable customer-assignment cost, and an expected-waiting-time cost. The expected-waiting-time cost results in a non-linear term in the objective function of the standard binary programming formulation of the problem. Thus, the solution …


Cost Functions Of Crabs: Applications Of Hermit Crab Shell Exchange Behavior To Vacancy Chain Modelling, Hannah Miele Apr 2021

Cost Functions Of Crabs: Applications Of Hermit Crab Shell Exchange Behavior To Vacancy Chain Modelling, Hannah Miele

Senior Honors Theses

Vacancy chain systems function as a method of resource distribution in domains such as housing and labor markets. Hermit crabs also employ vacancy chains as a method of shell exchange. Application of vacancy chain modelling in engineering has been attempted, but numerous flaws exist in the developed vacancy chain scheduling algorithm. This work addresses the lack of an appropriate vacancy chain cost function by developing a generalizable cost function based on hermit crab shell exchange behavior. The cost function’s purpose is enabling development of realistic engineering experiments and models based on real-world vacancy chain systems.


Digital Twin-Based Cooperative Control Techniques For Secure And Intelligent Operation Of Distributed Microgrids, Ahmed Aly Saad Ahmed Mar 2021

Digital Twin-Based Cooperative Control Techniques For Secure And Intelligent Operation Of Distributed Microgrids, Ahmed Aly Saad Ahmed

FIU Electronic Theses and Dissertations

Networked microgrids play a key role in constructing future active distribution networks for providing the power system with resiliency and reliability against catastrophic physical and cyber incidents. Motivated by the increasing penetration of renewable resources and energy storage systems in the distribution grids, utility companies are encouraged to unleash the capabilities of the distributed microgrid to work as virtual power plants that can support the power systems. The microgrids nature is transforming the grid and their control systems from centralized architecture into distributed architectures. The distributed networked microgrids introduced many benefits to the future smart grids, it created many challenges …


The Effects Of Customer Segmentation, Borrowers' Behaviours And Analytical Methods On The Performance Of Credit Scoring Models In The Agribusiness Sector, Daniela Lazo, Raffaella Calabrese, Cristian Bravo Roman Jan 2021

The Effects Of Customer Segmentation, Borrowers' Behaviours And Analytical Methods On The Performance Of Credit Scoring Models In The Agribusiness Sector, Daniela Lazo, Raffaella Calabrese, Cristian Bravo Roman

Statistical and Actuarial Sciences Publications

The main aim of this study is to analyse the joint effects of customer segmentation, borrowers' characteristics and modelling techniques on the classification accuracy of a scoring model for agribusinesses. To this end, we used data provided by a Chilean company on 161,163 loans from January 2007 to December 2013. We considered random forest, neural network and logistic regression models as analytical methods. Regarding the borrowers' profiles, we examined the effects of socio-demographic, repayment-behaviour, agribusiness-specific and credit-related variables. We also segmented the customers as individuals, SMEs and large holdings. As the segments show different risk behaviours, we obtained a better …


Fuzzy Cognitive Map-Based Knowledge Representation Of Hazardous Industrial Operations, Francesco Longo, Antonio Padovano, Letizia Nicoletti, Caterina Fusto, Mohaiad Elbasheer, Rafael Diaz Jan 2021

Fuzzy Cognitive Map-Based Knowledge Representation Of Hazardous Industrial Operations, Francesco Longo, Antonio Padovano, Letizia Nicoletti, Caterina Fusto, Mohaiad Elbasheer, Rafael Diaz

VMASC Publications

Hazardous industrial operations are highly stochastic, still human-dependent, and risky. Operators working in such an environment must understand the complex interrelation between several factors contributing to safe and effective operations. Therefore, being able to predict the effects of their actions on provoking or mitigating possible accidents is crucial. This study aims to utilize fuzzy cognitive maps (FCM) to model the expert’s reasoning about occupational health and safety (OHS) in confined space. This knowledge is used by operators to build their mental models. The developed FCM displays all the possible incidents of a confined space and links these incidents with all …


Methods For Weighting Decisions To Assist Modelers And Decision Analysts: A Review Of Ratio Assignment And Approximate Techniques, Barry Ezell, Christopher J. Lynch, Patrick T. Hester Jan 2021

Methods For Weighting Decisions To Assist Modelers And Decision Analysts: A Review Of Ratio Assignment And Approximate Techniques, Barry Ezell, Christopher J. Lynch, Patrick T. Hester

VMASC Publications

Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques …


Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz Jan 2021

Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz

VMASC Publications

Over the last few years, the Human Factors and Ergonomics (HF/E) discipline has significantly benefited from new human-centric engineered digital solutions of the 4.0 industrial age. Technologies are creating new socio-technical interactions between human and machine that minimize the risk of design-induced human errors and have largely contributed to remarkable improvements in terms of process safety, productivity, quality, and workers’ well-being. However, despite the Oil&Gas (O&G) sector is one of the most hazardous environments where human error can have severe consequences, Industry 4.0 aspects are still scarcely integrated with HF/E. This paper calls for a holistic understanding of the changing …


Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano Jan 2021

Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano

VMASC Publications

The defense shipbuilding and repair industry is a labor-intensive sector that can be characterized by low-product volumes and high investments in which a large number of shared resources, technology, suppliers, and processes asynchronously converge into large construction projects. It is mainly organized by the execution of a complex combination of sequential and overlapping stages. While entities engaged in this large-scale endeavor are often knowledgeable about their first-tier suppliers, they usually do not have insight into the lower tiers suppliers. A sizable part of any supply chain disruption is attributable to instabilities in sub-tier suppliers. This research note conceptually delineates a …


Comparing Greedy Constructive Heuristic Subtour Elimination Methods For The Traveling Salesman Problem, Petar Jackovich, Bruce A. Cox, Raymond R. Hill Dec 2020

Comparing Greedy Constructive Heuristic Subtour Elimination Methods For The Traveling Salesman Problem, Petar Jackovich, Bruce A. Cox, Raymond R. Hill

Faculty Publications

Purpose — This paper aims to define the class of fragment constructive heuristics used to compute feasible solutions for the traveling salesman problem (TSP) into edge-greedy and vertex-greedy subclasses. As these subclasses of heuristics can create subtours, two known methodologies for subtour elimination on symmetric instances are reviewed and are expanded to cover asymmetric problem instances. This paper introduces a third novel subtour elimination methodology, the greedy tracker (GT), and compares it to both known methodologies. Design/methodology/approach — Computational results for all three subtour elimination methodologies are generated across 17 symmetric instances ranging in size from 29 vertices to 5,934 …


Virginia Digital Shipbuilding Program (Vdsp): Building An Agile Modern Workforce To Improve Performance In The Shipbuilding And Ship Repair Industry, Joseph Peter Kosteczko, Katherine Smith, Jessica Johnson, Rafael Diaz Jun 2020

Virginia Digital Shipbuilding Program (Vdsp): Building An Agile Modern Workforce To Improve Performance In The Shipbuilding And Ship Repair Industry, Joseph Peter Kosteczko, Katherine Smith, Jessica Johnson, Rafael Diaz

VMASC Publications

Industry 4.0 is the latest stage in the Industrial Revolution and is reflected in the digital transformation and use of emergent technologies including the Internet of Things, Big Data, Robotic automation of processes, 3D printing and additive manufacturing, drones and Artificial Intelligence (AI) in the manufacturing industry. The implementation of these technologies in the Shipbuilding and Ship Repair Industry is currently in a nascent stage. Considering this, there is huge potential to increase cost savings, decrease production timelines, and drive down inefficiencies in Lifecyle management of ships. However, the implementation of these Industry 4.0 technologies is hindered by a noticeable …


Project Management Assignment Tool Using R And Shiny, Ben Stewart, Hoseok Jung, Moses Rawar Jan 2020

Project Management Assignment Tool Using R And Shiny, Ben Stewart, Hoseok Jung, Moses Rawar

Engineering and Technology Management Student Projects

Linear programs such as the R markdown language play an important role in helping to find an optimized solution in various fields of society. This area extends from the optimal distribution channels of coffee shops, which are closely related to our lives, to very important areas such as the deployment of military forces. Through this paper, we will try to find ways to maximize the efficiency and performance of a company by properly allocating project managers suitable for the projects performed by each company according to their capabilities and the requirements of the projects.


Short-Term Truckload Spot Rates' Prediction In Consideration Of Temporal And Between-Route Correlations, Wei Xiao, Chuan Xu, Hongling Liu, Hong Yang, Xiaobo Liu Jan 2020

Short-Term Truckload Spot Rates' Prediction In Consideration Of Temporal And Between-Route Correlations, Wei Xiao, Chuan Xu, Hongling Liu, Hong Yang, Xiaobo Liu

Computational Modeling & Simulation Engineering Faculty Publications

Truckload spot rate (TSR), defined as a price offered on the spot to transport a certain cargo by using an entire truck on a target transportation line, usually price per kilometer-ton, is a key factor in shaping the freight market. In particular, the prediction of short-term TSR is of great importance to the daily operations of the trucking industry. However, existing predictive practices have been limited largely by the availability of multilateral information, such as detailed intraday TSR information. Fortunately, the emerging online freight exchange (OFEX) platforms provide unique opportunities to access and fuse more data for probing the trucking …