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| TDDB56 | Algorithms and Optimization, 6 p (sw) /Algoritmer och optimering/ Advancement level: B | |
| Aim: Skills in mathematically modeling combinatorical optimization problems and find the complexity of these problems using complexity theory. Knowledge of well-known optimization problems and algorithms to solve them. Understanding of and skills in methods for design and analysis of algorithms. Knowledge about efficient implementations of basic abstract data types. Prerequisites: Linear algebra (e.g. TATA08), basic knowledge on abstract data types Supplementary courses: TDDA 32 Design and Analysis of Algorithms, TAOP 19 Combinatorical Optimization, Advanced Course Course organization: Lectures, tutorials, and laboratories. Course content: Basic linear programming and duality, problem classification, network problems (algorithms based on graph search), minimal spanning tree, tree search, non-optimizing algorithms (approximating algorithms and heuristics). Time complexity of algorithms, efficient implementations of abstract data types (list, stack, queue, mapping, tree, set, dictionary, priority queue, graph) , sorting and selection, methods for algorithm design (divide and conquer, dynamic programming, greedy algorithms). Course literature: Announced on course start. | ||
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