Modeling and Solving Constrained Optimization Problems
a.a. 2022/23
Responsabile didattico: Luca Di Gaspero
Durata: 28 ore
Programma: The course will provide the basic knowledge about Constrained Programming and related methodologies for solving real world discrete optimization problems. Constraint Programming basics: fundamental concepts, types of domains (finite domains, intervals, sets), constraints, search, branch and bound. CP modeling techniques: global constraints, redundant constraints, symmetry elimination, special-purpose constraints (e.g., scheduling), modeling of optimization problems, problem reduction. CP languages/libraries: MiniZinc, ILOG CP Optimizer. Modeling examples: n-Queens, Cryptoarithmetic, Sudoku, Scheduling, Timetabling, ... Basic solution methods: propagation, consistency, search. Advanced solution methods: heuristic methods, hybrid approaches, integration with heuristic/metaheuristic techniques. Statistical analysis of optimization algorithms. Lab practice.