Baski Balasundaram

Independent research for PhD dissertation requirement under direction of a member of the Graduate Faculty.Offered for variable credit, 1-15 credit hours, maximum of 30 credit hours.Prerequisite(s): Approval of major adviser and advisory committee.

Independent research for PhD dissertation requirement under direction of a member of the Graduate Faculty.Offered for variable credit, 1-15 credit hours, maximum of 30 credit hours.Prerequisite(s): Approval of major adviser and advisory committee.

Development and use of time value of money models. Bases for comparison of alternatives, including present worth, annual worth, rate of return and payout period methods. Decision-making among independent, dependent, capital-constrained and unequal-life projects. Replacement, breakeven and minimum cost analyses. Depreciation and depletion methods and their effect on corporate income taxes, leading to after-tax cash flow analysis. Introduction to financial reports.Prerequisite(s): MATH 2153 with grade of 'C' or better or MATH 2133 with grade of 'C' or better.

Network flows and combinatorial optimization models and algorithms with an emphasis on mathematical and algorithmic fundamentals. Covers basics of graph theory, algorithmic analysis, and complexity theory. Covers Classical Algorithms for shortest paths, minimum spanning trees, max-flow and min-cut, min-cost flows; P versus NP, traveling salesman problem, local search, metaheuristics, Christofides algorithm. Previously offered as IEM 6013.Prerequisite(s): IEM 5013 or equivalent.

Network flows and combinatorial optimization models and algorithms with an emphasis on mathematical and algorithmic fundamentals. Covers basics of graph theory, algorithmic analysis, and complexity theory. Covers Classical Algorithms for shortest paths, minimum spanning trees, max-flow and min-cut, min-cost flows; P versus NP, traveling salesman problem, local search, metaheuristics, Christofides algorithm. Previously offered as IEM 6013.Prerequisite(s): IEM 5013 or equivalent.

Independent research for PhD dissertation requirement under direction of a member of the Graduate Faculty.Offered for variable credit, 1-15 credit hours, maximum of 30 credit hours.Prerequisite(s): Approval of major adviser and advisory committee.

Development and use of time value of money models. Bases for comparison of alternatives, including present worth, annual worth, rate of return and payout period methods. Decision-making among independent, dependent, capital-constrained and unequal-life projects. Replacement, breakeven and minimum cost analyses. Depreciation and depletion methods and their effect on corporate income taxes, leading to after-tax cash flow analysis. Introduction to financial reports.Prerequisite(s): MATH 2153 with grade of 'C' or better or MATH 2133 with grade of 'C' or better.

A detailed investigation into one area of industrial engineering with a required written report.Offered for variable credit, 1-6 credit hours, maximum of 6 credit hours.

Introduction to mathematical optimization with an emphasis on linear, integer, network, and convex optimization. Effective formulization techniques, basic mathematical and algorithmic concepts, and software solution of large-scale problems arising in the practice of operations research, industrial and systems engineering, management sciences, and analytics.Prerequisite(s): IEM 4013 or equivalent.

Introduction to mathematical optimization with an emphasis on linear, integer, network, and convex optimization. Effective formulization techniques, basic mathematical and algorithmic concepts, and software solution of large-scale problems arising in the practice of operations research, industrial and systems engineering, management sciences, and analytics.Prerequisite(s): IEM 4013 or equivalent.

Research and thesis for master's students.Offered for variable credit, 1-6 credit hours, maximum of 6 credit hours.Prerequisite(s): Approval of major adviser.

Introduction to operations research, analytics, and mathematical optimization with an emphasis on topics in linear, integer, and network optimization. Effective model formulation and software solution of strategic, tactical and operational problems encountered in manufacturing, and service industries. Covers the simplex method, duality theory, sensitivity analysis, branch-and bound, network simplex, and Dijkstra's algorithm. Previously offered as IEM 4014.Prerequisite(s): MATH 3013 with grade of 'C' or better.

A detailed investigation into one area of industrial engineering with a required written report.Offered for variable credit, 1-6 credit hours, maximum of 6 credit hours.

Independent research for PhD dissertation requirement under direction of a member of the Graduate Faculty.Offered for variable credit, 1-15 credit hours, maximum of 30 credit hours.Prerequisite(s): Approval of major adviser and advisory committee.

Development and use of time value of money models. Bases for comparison of alternatives, including present worth, annual worth, rate of return and payout period methods. Decision-making among independent, dependent, capital-constrained and unequal-life projects. Replacement, breakeven and minimum cost analyses. Depreciation and depletion methods and their effect on corporate income taxes, leading to after-tax cash flow analysis. Introduction to financial reports.Prerequisite(s): MATH 2153 with grade of 'C' or better or MATH 2133 with grade of 'C' or better.

Research and thesis for master's students.Offered for variable credit, 1-6 credit hours, maximum of 6 credit hours.Prerequisite(s): Approval of major adviser.

Network flows and combinatorial optimization models and algorithms with an emphasis on mathematical and algorithmic fundamentals. Covers basics of graph theory, algorithmic analysis, and complexity theory. Covers Classical Algorithms for shortest paths, minimum spanning trees, max-flow and min-cut, min-cost flows; P versus NP, traveling salesman problem, local search, metaheuristics, Christofides algorithm. Previously offered as IEM 6013.Prerequisite(s): IEM 5013 or equivalent.

Network flows and combinatorial optimization models and algorithms with an emphasis on mathematical and algorithmic fundamentals. Covers basics of graph theory, algorithmic analysis, and complexity theory. Covers Classical Algorithms for shortest paths, minimum spanning trees, max-flow and min-cut, min-cost flows; P versus NP, traveling salesman problem, local search, metaheuristics, Christofides algorithm. Previously offered as IEM 6013.Prerequisite(s): IEM 5013 or equivalent.

Independent research for PhD dissertation requirement under direction of a member of the Graduate Faculty.Offered for variable credit, 1-15 credit hours, maximum of 30 credit hours.Prerequisite(s): Approval of major adviser and advisory committee.

Independent research for PhD dissertation requirement under direction of a member of the Graduate Faculty.Offered for variable credit, 1-15 credit hours, maximum of 30 credit hours.Prerequisite(s): Approval of major adviser and advisory committee.

Independent research for PhD dissertation requirement under direction of a member of the Graduate Faculty.Offered for variable credit, 1-15 credit hours, maximum of 30 credit hours.Prerequisite(s): Approval of major adviser and advisory committee.

Professionally supervised experience in a real-life problem involving authentic projects for which the student assumes a degree of professional responsibility. Activities must be approved in advance by the student's advisor. May consist of full or part-time engineering experience, on-campus or in industry, or both, either individually or as a responsible group member. Periodic reports, both oral and written, required as specified by the advisor. All eligible IEM 5020 credit hours should be included in the Plan of Study.Offered for variable credit, 1-6 credit hours, maximum of 6 credit hours.Prerequisite(s): Consent of School Head, approval of IEM advisor, and satisfactory completion of two consecutive regular (Fall/Spring) semesters.

Mathematical theory of linear optimization and the implications for algorithm development. Fundamentals of convex analysis, polyhedral sets, development of the simplex method, Farkas’ lemma, development of duality theory, sensitivity analysis, Dantzig-Wolfe decomposition, Benders decomposition, interior point algorithms. Previously offered as IEM 5033.Prerequisite(s): Concurrent Prerequisite IEM 5013 or consent of instructor.

Mathematical theory of linear optimization and the implications for algorithm development. Fundamentals of convex analysis, polyhedral sets, development of the simplex method, Farkas’ lemma, development of duality theory, sensitivity analysis, Dantzig-Wolfe decomposition, Benders decomposition, interior point algorithms. Previously offered as IEM 5033.Prerequisite(s): Concurrent Prerequisite IEM 5013 or consent of instructor.

Introduction to operations research, analytics, and mathematical optimization with an emphasis on topics in linear, integer, and network optimization. Effective model formulation and software solution of strategic, tactical and operational problems encountered in manufacturing, and service industries. Covers the simplex method, duality theory, sensitivity analysis, branch-and bound, network simplex, and Dijkstra's algorithm. Previously offered as IEM 4014.Prerequisite(s): MATH 3013 with grade of 'C' or better.