Topics in Operations Research and Decision Systems

This course introduces advanced optimization tools and techniques with the main emphasis being on the application of computational intelligence algorithms to different problems and cases which arise in business and industry, such as vehicle routing and scheduling problems, packing problems, facility location and layout problems, project scheduling with resource constraints problems, workforce and manpower scheduling problems, timetabling problems, machine scheduling problems, port logistics problems, telecom problems, waste management problems, health care problems, maritime and shipping problems.

On completion of this course, students should be able to:

• broaden their exposure to computational methodologies
• analyze and design effective computational intelligence algorithms for complex business problems
• provide examples and cases of how the computational intelligence algorithms can be used to solve real-life problems

The course material includes the following thematic areas:

• Threshold accepting algorithms 
• Tabu search algorithms 
• Swarm Intelligence and Ant colony optimization
• Evolutionary computation and genetic algorithms
• Scatter search and path relinking 
• Decision support systems and computational intelligence algorithms
• Examples and real life applications