Open Access. Powered by Scholars. Published by Universities.®

Operations Research, Systems Engineering and Industrial Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 17 of 17

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

Essays In Robust Optimization With Applications To Finance And Renewable Energy, Hao Jiang Dec 2023

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 …


Study Of Stochastic Market Clearing Problems In Power Systems With High Renewable Integration, Saumya Sakitha Sashrika Ariyarathne Oct 2022

Study Of Stochastic Market Clearing Problems In Power Systems With High Renewable Integration, Saumya Sakitha Sashrika Ariyarathne

Operations Research and Engineering Management Theses and Dissertations

Integrating large-scale renewable energy resources into the power grid poses several operational and economic problems due to their inherently stochastic nature. The lack of predictability of renewable outputs deteriorates the power grid’s reliability. The power system operators have recognized this need to account for uncertainty in making operational decisions and forming electricity pricing. In this regard, this dissertation studies three aspects that aid large-scale renewable integration into power systems. 1. We develop a nonparametric change point-based statistical model to generate scenarios that accurately capture the renewable generation stochastic processes; 2. We design new pricing mechanisms derived from alternative stochastic programming …


Heuristics For Capacity Allocation And Queue Assignment In Congested Service Systems With Stochastic Customer Demand And Immobile Servers, Adam Colley Oct 2022

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 Theses and Dissertations

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 …


Optimization Of Drive Time And Competitiveness In Sports League Design, Zhuo Chen Aug 2022

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 …


The Intersection Of Robotic Process Automation And Lean Six Sigma Applied To Unstructured Data, Emily Mcintosh May 2022

The Intersection Of Robotic Process Automation And Lean Six Sigma Applied To Unstructured Data, Emily Mcintosh

Operations Research and Engineering Management Theses and Dissertations

While new Artificial Intelligence (AI) technologies gain traction in the workplace, there seems to be more buzz around these newer advances, including Robotic Process Automation (RPA), than more established process improvement techniques such as Lean Six Sigma. This praxis research uses Lean Six Sigma as a framework for effectively deploying these emerging technologies, a challenge for 86% of companies (Ernst & Young, 2021). This research is applied to one of the legal industry’s most resource intensive processes – eDiscovery in the environment of a Big 4 accounting firm that provides services to corporations and legal professionals alike.

Electronic discovery (also …


Electricity Market Operations With Massive Renewable Integration: New Designs, Shengfei Yin Jul 2021

Electricity Market Operations With Massive Renewable Integration: New Designs, Shengfei Yin

Electrical Engineering Theses and Dissertations

Electricity market has been transitioning from a conventional and deterministic operation to a stochastic operation under the increasing penetration of renewable energy. Industry-level solutions toward the future electricity market operation ask for both accuracy and efficiency while maintaining model interpretability. Hence, reliable stochastic optimization techniques come to the first place for such a complex and dynamic problem.

This work starts at proposing a solution strategy for the uncertainty-based power system planning problem, which acts as a preliminary and instructs the electricity market operation. Considering 100% renewable penetration in the future, it analyzes the cost-effectiveness of renewable energy from a long-term …


Robust Optimization With Recourse In Portfolio Management: Theory And Applications To Stocks And Projects, Hedieh Ashrafi, Aurelie Thiele May 2021

Robust Optimization With Recourse In Portfolio Management: Theory And Applications To Stocks And Projects, Hedieh Ashrafi, Aurelie Thiele

Operations Research and Engineering Management Theses and Dissertations

Many real-world decision problems in engineering and management have uncertain parameters. Robust optimization methodology takes into account the uncertainty in parameters of the model in the decision-making framework. In robust optimization methodology, we assume we do not know the probability distribution of parameters, and we have partial information about parameters. Portfolio management is one of those famous applications that have an uncertain environment. So, for this application, robust methodology would be a good choice. This dissertation contains three main works as the following:\\ In the first work, we provided the combination of European options and a robust optimization model to …


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 …


A Data-Driven Framework For Decision Making Under Uncertainty: Integrating Markov Decision Processes, Hidden Markov Models And Predictive Modeling, Hossein Kamalzadeh May 2020

A Data-Driven Framework For Decision Making Under Uncertainty: Integrating Markov Decision Processes, Hidden Markov Models And Predictive Modeling, Hossein Kamalzadeh

Operations Research and Engineering Management Theses and Dissertations

The problem of decision making under uncertainty can be broken down into two parts. First, how do we learn about the world? This involves the problem of modeling the system and its uncertainty. Secondly, given what we currently know about the world, how should we decide what to do, taking into account uncertainty of future events and observations that may change our conclusions. Many systems evolve over time and often the next state of the system is not known with certainty, often modeled as a probability distribution over system states. Dealing with such systems especially when we can make a …


Resource Allocation And Task Scheduling Optimization In Cloud-Based Content Delivery Networks With Edge Computing, Yang Peng Dec 2019

Resource Allocation And Task Scheduling Optimization In Cloud-Based Content Delivery Networks With Edge Computing, Yang Peng

Operations Research and Engineering Management Theses and Dissertations

The extensive growth in adoption of mobile devices pushes global Internet protocol (IP) traffic to grow and content delivery network (CDN) will carry 72 percent of total Internet traffic by 2022, up from 56 percent in 2017. In this praxis, Interconnected Cache Edge (ICE) based on different public cloud infrastructures with multiple edge computing sites is considered to help CDN service providers (SPs) to maximize their operational profit. The problem of resource allocation and performance optimization is studied in order to maximize the cache hit ratio with available CDN capacity.

The considered problem is formulated as a multi-stage stochastic linear …


Generalized Relay Network Design And Collaborative Dispatching In Truckload Transportation, Amin Ziaeifar Oct 2019

Generalized Relay Network Design And Collaborative Dispatching In Truckload Transportation, Amin Ziaeifar

Operations Research and Engineering Management Theses and Dissertations

The truckload industry faces a serious problem of high driver shortage and turnover rate which is typically around 100\%. Among the major causes of this problem are extended on-the-road times where drivers handle several truckload pickup and deliveries successively; non-regular schedules and get-home rates; and low utilization of drivers dedicated time. These are by-and-large consequences of the driver-to-load dispatching method, which is based on point-to-point dispatching or direct shipment from origin-to-destination, commonly employed in the industry. In this dissertation, we consider an alternative dispatching method that necessitates careful design of an underlying network. In this scheme, a truckload on its …


Backhaul Profit Maximization Problem Instances, Yuanyuan Dong, Yulan Bai, Eli V. Olinick, Andrew Junfang Yu Aug 2019

Backhaul Profit Maximization Problem Instances, Yuanyuan Dong, Yulan Bai, Eli V. Olinick, Andrew Junfang Yu

Operations Research and Engineering Management

This archive contains data for the problem instances described in the technical report "An Empirical Study of Mixed Integer Programming Formulations of the Backhaul Profit Maximization Problem" by Yulan Bai and Eli V. Olinick.


An Empirical Study Of Mixed Integer Programming Formulations Of The Backhaul Profit Maximization Problem, Yulan Bai, Eli V. Olinick Aug 2019

An Empirical Study Of Mixed Integer Programming Formulations Of The Backhaul Profit Maximization Problem, Yulan Bai, Eli V. Olinick

Operations Research and Engineering Management

Solving an instance of the Backhaul Profit Maximization Problem (BPMP) requires simultaneously solving two problems: (1) determining how to route an empty delivery vehicle back from its current location to its depot by a scheduled arrival time, and (2) selecting a profit-maximizing subset of delivery requests between various locations on the route subject to the vehicle's capacity. We propose and test a series of enhancements to the node-arc and triples mixed integer programming formulations of BPMP found in the literature and develop a multi-criteria Composite Index Method (CIM) to evaluate the results. We find that CPLEX takes 5 to 34 …


Extreme-Point Tabu Search Heuristics For Fixed-Charge Generalized Network Problems, Angelika Leskovskaya Aug 2019

Extreme-Point Tabu Search Heuristics For Fixed-Charge Generalized Network Problems, Angelika Leskovskaya

Operations Research and Engineering Management Theses and Dissertations

While researchers have studied generalized network flow problems extensively, the powerful addition of fixed charges on arcs has received scant attention. This work describes network-simplex-based algorithms that efficiently exploit the quasi-tree basis structure of the problem relaxations, proposes heuristics that utilize a candidate list, a tabu search with short and intermediate term memories to do the local search, a diversification approach to solve fixed-charge transportation problems, as well as a dynamic linearization of objective function extension for the transshipment fixed-charge generalized problems. Computational testings for both heuristics demonstrate their effectiveness in terms of speed and quality of solutions to these …


Equilibrium-Based Workload Balancing For Robust Emergency Response Operations In Metropolitan Areas, Parya Roustaee Apr 2019

Equilibrium-Based Workload Balancing For Robust Emergency Response Operations In Metropolitan Areas, Parya Roustaee

Civil and Environmental Engineering Theses and Dissertations

This thesis presents an equilibrium-based modeling framework for emergency response (ER) workload balancing to achieve robust operation in large-scale metropolitan areas. The problem is formulated as a non-linear mathematical program (NLP), which determines the optimal workload cutoff for each ER station such that the weighted sum of the area-wide expected response time and its variation are minimized. The concept of Marginal Cost of Uncertainty (MCU) is introduced to measure the impact of a station’s workload increase on the area-wide service performance. The solution of the NLP is proved to be equivalent to a state of equilibrium in which all stations …


Network Design For In-Motion Wireless Charging Of Electric Vehicles: Models And Algorithms, Mamdouh Mubarak Oct 2018

Network Design For In-Motion Wireless Charging Of Electric Vehicles: Models And Algorithms, Mamdouh Mubarak

Operations Research and Engineering Management Theses and Dissertations

The aim of this research is to study the optimal deployment of wireless charging stations (WCS) in urban transportation networks. It is widely acknowledged that the relatively short driving range of EV and the long battery charging times collectively lead to a phenomenon known as "range anxiety" of EV drivers. This phenomenon remains to be the major factor that hampers EV adoption. Thus, in this dissertation, we study a cost-effective deployment plan of WCSs that facilitates EV adoption by alleviating the two major causes of the “range anxiety” phenomenon.

In the first part of this dissertation, we propose a deployment …


Maximizing Financial Benefit Of Lean Six Sigma Projects Through Optimized Selection Criteria, Colin Wasiloff Oct 2018

Maximizing Financial Benefit Of Lean Six Sigma Projects Through Optimized Selection Criteria, Colin Wasiloff

Operations Research and Engineering Management Theses and Dissertations

As evolving threats across the globe keep pace with increasing budget constraints, the US Army’s major subordinate commands and their sub-organizations are constantly challenged to do more with less. Resources such as human capital, information technology, facilities, and budgeted funding are stretched as thin as ever, while requirements to serve the Warfighter remain paramount. Each dollar of financial benefit gained through cost reduction efforts at the US Army can affect the Warfighter directly. Budgeted money saved or avoided is reprogrammed both locally and atop the hierarchy at the Department of Treasury to serve the Warfighter better.

Ordinal Logistic Regression was …