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This is an advanced algorithms course. It covers material from optimisation algorithms and combinatorial problem solving. It introduces stochastic local search (SLS) algorithms, such as stochastic hill-climbing, simulated annealing, tabu search, evolutionary algorithms, and ant colony optimization. SLS algorithms are among the most prominent and successful techniques for solving computationally hard problems. For demonstrating the applicability of these algorithms, we will use different combinatorial problems, such as the satisfiability problem in propositional logic and the travelling salesman problem. Students will have the opportunity to learn established and cutting edge practices and methodologies in this important research area. The course is composed of weekly lectures, formal and informal discussions, and two assignments.
Faculty Policy - Unit Assessment Hurdles
Task 1 (40%)
Task 2 (20%)