Established originally as a Program at Georgia Tech in 1924, becoming a School in 1945, the School of Industrial and Systems Engineering (ISyE) is the largest academic program of its kind in the United States. With nearly 65 tenure-track faculty, ISyE is able to support not only a broad spectrum of academic concentrations but, importantly, several that have achieved world-class rank. Though the School functions administratively as a single cohesive unit, some of our sub-disciplines or academic specialties are so large and concentrated, they could be legitimately viewed as academic departments in their own right.

ISyE's mission is the creation, assimilation, integration, and dissemination of knowledge involving industrial and systems engineering. In carrying out its educational mission, ISyE seeks to develop a high potential population of full-time, traditional students at the undergraduate and graduate levels as well as those in industry and government who need to acquire new and updated skills for positions of leadership in engineering, academia, and management.

Specifically, ISyE seeks to:

  • Provide selected research and services to industry and government which meet their specific needs;
  • Contribute to the advancement of the ISyE profession through faculty leadership;
  • Facilitate the interface among industries, problems and methodologies; and
  • Enhance the overall reputation of Georgia Tech.

Industrial and Systems Engineering at Georgia Tech will be the world's leader in expanding and communicating engineering knowledge and innovation associated with designing, operating and improving sustainable processes for acquiring, producing, selling and delivering products and services.

Collections in this community

Recent Submissions

  • An Investigation of Model-Based Approaches in Solving a Variety of Global Optimization Problems 

    Hale, Joshua Q (Georgia Institute of Technology, 2017-04-03)
    Model-based optimization methods are a class of random search methods that are useful for solving global optimization problems. These types of methods have shown significant empirical success in solving a multitude of ...
  • A Reduction Framework for Approximate Extended Formulations and a Faster Algorithm for Convex Optimization 

    Zink, Daniel (Georgia Institute of Technology, 2017-04-06)
    Linear programming (LP) and semidefinite programming (SDP) are among the most important tools in Operations Research and Computer Science. In this work we study the limitations of LPs and SDPs by providing lower bounds on ...
  • Scaling-based Methods in Optimization and Cut Generation 

    Pavelka, Jeffrey William (Georgia Institute of Technology, 2017-03-30)
    This thesis addresses both theoretical and practical concerns in integer programming. In Chapter 2 we discuss scaling-based primal methods for integer programming. Such methods optimize by repeatedly solving augmentation ...
  • Estimation and Optimization Problems in Revenue Management with Customer Choice Behavior 

    Ding, Weijun (Georgia Institute of Technology, 2017-01-13)
    The first part of the thesis studies the parameter estimation problem in revenue management with discrete choice models. Revenue management models that include customer choice behavior have among others two types of ...
  • Sparsity in Integer Programming 

    Iroume, Andres (Georgia Institute of Technology, 2017-01-11)
    Sparse input data is data in which most of the data coefficients are zero. Many areas of scientific computing and optimization have been very successful in harnessing the effect of sparsity of input data to improve the ...
  • Combined Objective Least Squares and Long Step Primal Dual Subproblem Simplex Methods 

    Xu, Sheng (Georgia Institute of Technology, 2016-04-27)
    The first part of this research work is based on Combined Objective Least Squares (COLS). We took a deeper look at matrix decomposition algorithms that are the dominating components in COLS algorithms, in terms of computational ...
  • Riding Technology Waves: Opportunities for Operations Research 

    Dietrich, Brenda (Georgia Institute of Technology, 2017-03-30)
    Brenda Dietrich's talk includes a fly-by of five decades of information technology beginning with its use to automate business processes and extending to its current role in intermediating social processes. The resulting ...
  • Resource allocation algorithms in stochastic systems 

    Suk, Tonghoon (Georgia Institute of Technology, 2016-11-15)
    My dissertation work examines resource allocation algorithms in stochastic systems. I use applied probability methodology to investigate large-scaled stochastic systems. Specifically, my research focuses on proposing and ...
  • Theory and computation of sparse cutting planes 

    Wang, Qianyi (Georgia Institute of Technology, 2016-11-09)
    Cutting plane plays an important role in the theory and computation of integer programming. Nowadays, most state-of-the-art integer programming solvers tend to bias their cutting plane selection towards sparse ones, which ...
  • Cost-effective management of chronic diseases: surveillance, treatment, and elimination 

    Chen, Qiushi (Georgia Institute of Technology, 2016-11-15)
    Chronic diseases have become the most common health problems worldwide. The cost of chronic disease management continues to rise, leading to a substantial economic burden to both patients and society. Mathematical models ...
  • Novel Statistical Learning and Data Mining Methods for Service Systems Improvement 

    Ranjan, Chitta (Georgia Institute of Technology, 2016-11-07)
    This dissertation focuses on solving problems for service systems improvement using newly developed data mining methods. Among a large plethora of problems in this realm, this dissertation attempts to solve three distinct ...
  • Performance Optimization of Complex Resource Allocation Systems 

    Li, Ran (Georgia Institute of Technology, 2016-09-13)
    The typical control objective for a sequential resource allocation system (RAS) is the optimization of some (time-based) performance index, while ensuring the logical/behavioral correctness of the underlying automated ...
  • Computational Analysis of Technological Innovation in Complex Enterprise Systems 

    Park, Hyunwoo (Georgia Institute of Technology, 2015-11-16)
    Technological innovation in complex enterprise systems requires coordinated interplay between a heterogeneous set of industrial players. The complexity in how firms form relationships with each other perplexes the ...
  • Large-Scale Unit Commitment: Decentralized Mixed Integer Programming Approaches 

    Feizollahi, Mohammadjavad (Georgia Institute of Technology, 2015-08-19)
    We investigate theory and application of decentralized optimization for mixed integer programming (MIP) problems. Our focus is on loosely coupled MIPs where different blocks of the problem have mixed integer linear feasible ...
  • Dynamic optimization for same-day delivery operations 

    Klapp Belmar, Mathias A. (Georgia Institute of Technology, 2016-11-15)
    Same-day delivery (SDD) is a service where consumers place orders online on the same day that these are processed and delivered to the customer. Providing a delivery service requires order management at the stocking location ...
  • Predictive maintenance management using sensor-based degradation models 

    Gebraeel, Nagi Z. (Georgia Institute of Technology, 2008-06-30)
    This paper presents a sensory-updated degradation-based predictive maintenance (SUDM) policy. The proposed maintenance policy utilizes contemporary degradation models that combine component-specific real-time degradation ...
  • Belt Line Feasibility Study: Final Report 

    Cha, Jane; Dimassi, Mike; Haynes, Derek; Kwak, Jean; Mian, Salman; Murphy, Ryan; Nedev, Nikolay; Riaz, Nabil; Zeller, Jason (Georgia Institute of Technology, 2003-04)
    The overall objective of this study is to assist the Atlanta City Council and URS in determining the feasibility of implementing a light rail system proposal to help alleviate Atlanta’s traffic and pollution problems and ...
  • Minimum energy designs: Extensions, algorithms, and applications 

    Gu, Li (Georgia Institute of Technology, 2016-07-27)
    Minimum Energy Design (MED) is a recently proposed technique for generating deterministic samples from any arbitrary probability distribution. Most space-filling designs look for uniformity in the region of interest. In ...
  • Optimal admission control in tandem and parallel queueing systems with applications to computer networks 

    Silva Izquierdo, Daniel F. (Georgia Institute of Technology, 2016-07-25)
    Modern computer networks require advanced, efficient algorithms to control several aspects of their operations, including routing data packets, access to secure systems and data, capacity and resource allocation, task ...
  • Robust optimization for renewable energy integration in power system operations 

    Lorca Galvez, Alvaro Hugo (Georgia Institute of Technology, 2016-07-20)
    Optimization provides critical support for the operation of electric power systems. As power systems evolve, enhanced operational methodologies are required, and innovative optimization models have the potential to support ...

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