Optimization problems are frequently encountered in almost all disciplines of science and engineering. This course will familiarize the audience with both mathematical and computational intelligence algorithms to solve combinatorial optimization problems. The course is designed so as to enable the participants to quickly use state-of-the-art tools to solve optimization problems. A unique feature of this course will be discussion of a realistic case study to thoroughly understand various aspects of optimization. INTENDED AUDIENCE : Students, Researchers & Working ProfessionalsPREREQUISITES : Basic MathematicsINDUSTRY SUPPORT : All
Computer Aided Applied Single Objective Optimization
Indian Institute of Technology Guwahati and NPTEL via Swayam
Overview
Syllabus
Week 1: IntroductionWeek 2: RegressionWeek 3: Teaching Learning Based OptimizationWeek 4: Particle Swarm OptimizationWeek 5: Differential EvolutionWeek 6: Genetic AlgorithmWeek 7: Artificial Bee Colony OptimizationWeek 8: Constraint Handling & Result Analysis
Week 9:Linear & Mixed Integer Linear Programming
Week 10:Solution of Case Study with Mathematical & CI Techniques
Week 11:MATLAB Optimization Toolbox
Week 12:GAMS & IBM ILOG Optimization Studio
Week 9:Linear & Mixed Integer Linear Programming
Week 10:Solution of Case Study with Mathematical & CI Techniques
Week 11:MATLAB Optimization Toolbox
Week 12:GAMS & IBM ILOG Optimization Studio
Taught by
Prof. Prakash Kotecha
