Optimization Program in Interdisciplinary Studies

An optimization problem asks to find a minimum (or a maximum) of a function subject to constraints.  Optimization problems are of fundamental importance in mathematics, computer science, engineering and related areas.  In applications, solutions of optimization problems may correspond to optimal scheduling assignments, optimal treatment plans for radiation therapy, and optimal investment strategies.

Optimization is inherently interdisciplinary, lying at the intersection of mathematics, computer science, engineering, economics, and related disciplines.  It has a rich history that can be traced back to the foundation of calculus.  Nowadays, optimization is a particularly exciting and vibrant area - recently discovered tools and algorithms make it possible to solve problems that were previously considered computationally impossible.

Core program:

The MSc IGS Optimization theme requires at least 6 credits in method courses, and at least 6 credits in topic courses. It is recommended that out of the minimum of 18 credits required for the MSc, 3 credits be taken in seminar courses. The PhD IGS Optimization theme requires at least 3 credits in method courses, and at least 9 credits in topic courses. See the Okanagan Academic Calendar - Program Requirements.

Method Courses

  • IGS 501 (Interdisciplinary Research Methods)
  • IGS 509 (Directed Studies in Interdisciplinary Research Methods)
  • IGS 601 (Advanced Topics in Research Methods and Analysis)
  • MATH 523 (Combinatorial Optimization)
  • MATH 563 (Convex Analysis and Optimization)

The following courses must be cross-listed as IGS 501 or IGS 509, and will count as a method course:   

  •  COSC 302 (Numerical Computation for Algebraic Problems)
  •  COSC 303 (Numerical Approximation and Discretization)
  • COSC 320 (Analysis of Algorithms)
  • COSC 405 (Modeling & Simulation)

Topic courses

  • IGS 520 (Special Topics in Interdisciplinary Studies)
  • IGS 540 (Special Topics in Optimization)
  • IGS 549 (Directed Studies in Optimization)
  • IGS 620 (Advanced Topics in Interdisciplinary Studies)
  • MATH 570 (optimization and analysis I)
  • MATH 601 (topics in analysis) Always cross-listed as MATH 430; grad students should take MATH 601
  • MATH 604 (topics in optimization)
  • MATH 605 (topics in applied mathematics)
  • MATH 670 (optimization and analysis II)

The following courses must be cross-listed as IGS 540 or IGS 549, and will count as a topic course:

  • MATH 441 (Modeling of Discrete Optimization Problems) 
  • MATH 442 (Optimization in Graphs and Networks)
  • COSC 406 (Numerical Optimization)
  • COSC 407 (Parallel Computing)
  • COSC 416 (Special Topics in Databases)
  • COSC 417 (Topics in Computer Networks)
  • COSC 419 (Special Topic)
  • COSC 448 (Directed Studies in Computer Science)      

Seminar courses

  • MATH 590 (grad seminar, 1 credit); (undergrad equiv course is MATH 448; grad students should take MATH 590)
  • IGS 524 (proseminar in optimization)

Other courses

(courses that can be used in the program but do not count towards the method or topic requirement):

  • ENGR 502 (technical communication)

Note: Additional courses to meet the theme requirements may be approved by the IGS program coordinator.   

UBC Okanagan campus IGS Optimization theme committee:

  • H. Bauschke (Convex Analysis, Mathematics)
  • Y. Gao (Discrete Optimization, Computer Science)
  • W. Hare (Nonsmooth Analysis, Mathematics)
  • J. Loeppky (Design and Analysis of Experiments, Statistics)
  • Y. Lucet , Program Coordinator - IGS Optimization theme. (Numerical Optimization, Computer Science)
  • S. Tesfamariam (Risk Analysis, Civil Infrastructure Management, Civil Engineering)
  • S. Wang (Nonsmooth Analysis, Mathematics)

These researchers are actively involved in training graduate students in optimization. For more information, consult the faculty member webpage and contact him directly. Regular seminars on optimization are offered by the Centre for Optimization, Convex Analysis, and Nonsmooth Analysis (COCANA).

Last reviewed shim10/17/2014 10:27:25 AM