At ISyE, we work on ways to improve a variety of complex systems by formulating and analyzing abstract models in search of making systems more efficient and optimizing performance. We address how people and the decisions they make contribute to the complexity of systems and how people benefit when those systems are analyzed. We immerse ourselves in the depth and breadth of decision-based technical problem solving by focusing on the disciplines of industrial engineering, operations research, and systems engineering.
Students come to our academic programs with a variety of career objectives and from a host of disciplines and academic interests.
At the undergraduate level, many find the fields’ characteristic flexibility appealing. Our BSIE curriculum provides the technical expertise that one would expect in an engineering major. It also provides excellent preparation to function in a great breadth of professional settings such as manufacturing, logistics, economic and financial modeling, transportation, consulting, health and humanitarian logistics, etc.
At the master’s level, this same appeal holds true.
At the Ph.D. level, students are just as likely to be attracted by the inherent complexity of our problem domains as well as the sophistication and variety of our problem-solving methodologies. In addition to representation by a variety of engineering disciplines, many of our students in ISyE earned prior degrees in other fields such as mathematics, statistics, and computer science.
Industrial engineering is concerned with the design, improvement and installation of integrated systems of people, materials, information, equipment and energy. It draws upon specialized knowledge and skill in the mathematical, physical, and social sciences together with the principles and methods of engineering analysis and design, to specify, predict, and evaluate the results to be obtained from such systems.
Operations Research is a discipline that deals with the application of advanced analytical methods to help make better decisions. The terms management science and analytics are sometimes used as synonyms for operations research.
Employing techniques from other mathematical sciences, such as mathematical modeling, statistical analysis, and mathematical optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems.
Operations research overlaps with other disciplines, notably industrial engineering and operations management. It is often concerned with determining a maximum (such as profit, performance, or yield) or minimum (such as loss, risk, or cost.)
Operations research encompasses a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency, such as simulation, mathematical optimization, queuing theory, Markov decision processes, economic methods, data analysis, statistics, neural networks, expert systems, and decision analysis. Nearly all of these techniques involve the construction of mathematical models that attempt to describe the system.
Because of the computational and statistical nature of most of these fields, O.R. also has strong ties to computer science. Operations researchers faced with a new problem must determine which of these techniques are most appropriate given the nature of the system, the goals for improvement, and constraints on time and computing power.
Systems Engineering is an interdisciplinary approach and means to enable the realization of successful systems. It focuses on defining customer needs and required functionality early in the development cycle, documenting requirements, then proceeding with design synthesis and system validation while considering the complete problem: