IE 431 Introduction to Optimization Theory Fall 2019

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IE 431 Introduction to Optimization Theory Fall 2019

IE 431 Introduction to Optimization Theory Fall 2019

q Instructor: Sungsoo Park (sspark@kaist. ac. kr), Building E 2 -2, room 4112, Tel:

q Instructor: Sungsoo Park ([email protected] ac. kr), Building E 2 -2, room 4112, Tel: 3121 Office hour: Mon, Wed 13: 00 – 14: 30 or by appointment (telephone/email) q Class hours: Tue, Thr 14: 30 – 16: 00 q Class room: IE building(E 2 -2) 1120 q TA: Jaehee Jeong (jh [email protected] ac. kr) Building E 2 -2, room 4113, Tel: 3161 Office hour: Mon, Wed, Fr 14: 30 -16: 30 or by appointment q Homepage: http: //solab. kaist. ac. kr/, download class notes, homeworks. Opt Theory 2019 2

q Text: “Optimization in Operations Research”, Ronald L. Rardin, Pearson, 1998, 1 st edition,

q Text: “Optimization in Operations Research”, Ronald L. Rardin, Pearson, 1998, 1 st edition, international student edition available. (2017, 2 nd edition) q Bring your text to the class q Grading: Midterm 30 - 40%, Final 40 - 50%, (closed book/notes) Homework 10 - 15% (Including SW use, CPLEX/Xpress-MP) q Characteristics of the course Ø Emphasis on optimization models and algorithms beyond linear program Ø Need understanding of linear program theory and algorithms as background. We do not spend time on LP itself in this course. (We may review important results on linear program briefly if needed) Ø Prerequisite: IE 331 OR-Optimization or consent of instructor. Opt Theory 2019 3

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Origins of OR q Tentative course schedule • Introduction, Multiobjective optimization, Goal programming (1

Origins of OR q Tentative course schedule • Introduction, Multiobjective optimization, Goal programming (1 week) • Networks (shortest paths), dynamic programming (2 weeks) • Networks (optimal flows) (2 weeks) • Networks (maximum flows, trees) (1 week) • Discrete optimization (models) (1 week) • Midterm examination (1 week) • Discrete optimization (algorithms) (2 weeks) • Large scale optimization (relaxation, decomposition) (1 week) • Nonlinear programming (unconstrained problems) (2 weeks) • Nonlinear programming (constrained problems) (2 weeks) • Final examination (1 week) Opt Theory 2019 5