Operations Research and Computational Intelligence

    Course Code: 
    8144
    Semester: 
    6th
    Specialization Courses
    Professor: 

    MANOUSAKIS ELEFTHERIOS

    Course Description

    The course material includes the following thematic areas:

    • Metaheuristic methods for optimizing a solution: Local Search, GRASP, Tabu Search, Iterated Local Search and Guided Local Search
    • Metaheuristic methods for optimizing a population of solutions: Ant Colony Optimization, Swarm Intelligence and evolutionary algorithms
    • Modeling classical optimization problems with emphasis on Logistics problems
    • Mathematical programming using Gurobi
    • Constraint Programming
    • Matheuristics and hybrid approaches to computational intelligence
    • Applications of Operations Research in industry and its connection with Software Engineering

    Learning Outcomes

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

    1. Understand the basic principles of metaheuristic algorithms of computational intelligence and will choose appropriate methods for different optimization problems.
    2. Develop models for complex decision problems using mathematical programming techniques.
    3. Implement optimization algorithms in Python and will evaluate their effectiveness.
    4. Develop hybrid approaches by combining different methods.
    5. Critically address computational problems beyond the field of Operations Research