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Articles 1 - 10 of 10
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Benefits Of Pre-Construction Analysis: Cet Senior Capstone Expands Understanding Of An Urban Refuge At Gallopnyc Sunrise Stables, Aalaa Mohammed
Benefits Of Pre-Construction Analysis: Cet Senior Capstone Expands Understanding Of An Urban Refuge At Gallopnyc Sunrise Stables, Aalaa Mohammed
Publications and Research
For any construction project, there exists a phase of planning known as “pre-construction.” This initial phase of the project provides a definition of the project, identification of potential issues, planning and scheduling, scope, cost estimation, and analysis of needs for the job. My research analyzes a pre-construction case study conducted for Gallop NYC’s Stable in Howard Beach, Queens. The findings suggest that the practice of construction planning is effective in order to avoid delays in construction itself and ensure successful project completion. Supporting literature examines some of the best practices for pre-construction analysis. These include but are not limited to: …
Quantifying Controllability In Temporal Networks With Uncertainty, James C. Boerkoel Jr., Lindsay Popowski, Michael Gao, Hemeng Li, Savana Ammons, Shyan Akmal
Quantifying Controllability In Temporal Networks With Uncertainty, James C. Boerkoel Jr., Lindsay Popowski, Michael Gao, Hemeng Li, Savana Ammons, Shyan Akmal
All HMC Faculty Publications and Research
Controllability for Simple Temporal Networks with Uncertainty (STNUs) has thus far been limited to three levels: strong, dynamic, and weak. Because of this, there is currently no systematic way for an agent to assess just how far from being controllable an uncontrollable STNU is. We provide new insights inspired by a geometric interpretation of STNUs to introduce the degrees of strong and dynamic controllability - continuous metrics that measure how far a network is from being controllable. We utilize these metrics to approximate the probabilities that an STNU can be dispatched successfully offline and online respectively. We introduce new methods …
Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar
Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar
Research Collection School Of Computing and Information Systems
We address the problem of multiple agents finding their paths from respective sources to destination nodes in a graph (also called MAPF). Most existing approaches assume that all agents move at fixed speed, and that a single node accommodates only a single agent. Motivated by the emerging applications of autonomous vehicles such as drone traffic management, we present zone-based path finding (or ZBPF) where agents move among zones, and agents' movements require uncertain travel time. Furthermore, each zone can accommodate multiple agents (as per its capacity). We also develop a simulator for ZBPF which provides a clean interface from the …
Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Research Collection School Of Computing and Information Systems
Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such …
Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Research Collection School Of Computing and Information Systems
Cross-docking is considered as a method to manage and control the inventory flow, which is essential in the context of supply chain management. This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD which has been extensively studied due to its ability to reducethe overall costs occurring in a supply chain network. Given a fleet of homogeneous vehicles for delivering a single type of product from suppliers to customers through a cross-dock facility, the objective of VRPCD is to determine the number of vehicles used and the corresponding vehicle routes, such that the vehicleoperational and transportation …
A Matheuristic Algorithm For Solving The Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
A Matheuristic Algorithm For Solving The Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Research Collection School Of Computing and Information Systems
This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD. The aim is to find a set of routes to deliver single products from a set of suppliers to a set of customers through a cross-dock facility, such that the operational and transportation costs are minimized, without violating the vehicle capacity and time horizon constraints. A two-phase matheuristic approach that uses the routes of the local optima of an adaptive large neighborhood search (ALNS) as columns in a set-partitioning formulation of the VRPCD is designed. This matheuristic outperforms the state-of-the-art algorithms in solving a subset of …
A New Intra-Cluster Scheduling Scheme For Real-Time Flows In Wireless Sensor Networks, Gohar Ali, Fernando Moreira, Omar Alfandi, Babar Shah, Mohammed Ilyas
A New Intra-Cluster Scheduling Scheme For Real-Time Flows In Wireless Sensor Networks, Gohar Ali, Fernando Moreira, Omar Alfandi, Babar Shah, Mohammed Ilyas
All Works
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Real-time flows using time division multiple access (TDMA) scheduling in cluster-based wireless sensor networks try to schedule more flows per time frame to minimize the schedule length to meet the deadline. The problem with the previously used cluster-based scheduling algorithm is that intra-cluster scheduling does not consider that the clusters may have internal or outgoing flows. Thus, intra-cluster scheduling algorithms do not utilize their empty time-slots and thus increase schedule length. In this paper, we propose a new intra-cluster scheduling algorithm by considering that clusters may have having internal or outgoing …
Integration Of Forecasting, Scheduling, Machine Learning, And Efficiency Improvement Methods Into The Sport Management Industry, Caleb Mcgrady
Integration Of Forecasting, Scheduling, Machine Learning, And Efficiency Improvement Methods Into The Sport Management Industry, Caleb Mcgrady
Senior Honors Theses
Sport management is a complicated and economically impactful industry and involves many crucial decisions: such as which players to retain or release, how many concession vendors to add, how many fans to expect, what teams to schedule, and many others are made each offseason and changed frequently. The task of making such decisions effectively is difficult, but the process can be made easier using methods of industrial and systems engineering (ISE). Integrating methods such as forecasting, scheduling, machine learning, and efficiency improvement from ISE can be revolutionary in helping sports organizations and franchises be consistently successful. Research shows areas including …
Law School News: F.A.Q. Update: Covid-19 And Rwu Law 03-30-2020, Roger Williams University School Of Law
Law School News: F.A.Q. Update: Covid-19 And Rwu Law 03-30-2020, Roger Williams University School Of Law
Life of the Law School (1993- )
No abstract provided.
Spatial Indexing For System-Level Evaluation Of 5g Heterogeneous Cellular Networks, Roohollah Amiri, Eren Balevi, Jeffrey G. Andrews, Hani Mehrpouyan
Spatial Indexing For System-Level Evaluation Of 5g Heterogeneous Cellular Networks, Roohollah Amiri, Eren Balevi, Jeffrey G. Andrews, Hani Mehrpouyan
Electrical and Computer Engineering Faculty Publications and Presentations
System level simulations of large 5G networks are essential to evaluate and design algorithms related to network issues such as scheduling, mobility management, interference management, and cell planning. In this paper, we look back to the idea of spatial indexing and its advantages, applications, and future potentials in accelerating large 5G network simulations. We introduce a multi-level inheritance based architecture which is used to index all elements of a heterogeneous network (HetNet) on a single geometry tree. Then, we define spatial queries to accelerate searches in distance, azimuth, and elevation. We demonstrate that spatial indexing can accelerate location-based searches by …