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CS 312: Algorithm Analysis

This work is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License. CS 312: Algorithm Analysis. Lecture # 39: Problem Solving. Credit: Eric Ringger. A Rough-Draft Set of Questions for Problem Solving. Problem-Solving. Problem Formulation Algorithm Design

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CS 312: Algorithm Analysis

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  1. This work is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License. CS 312: Algorithm Analysis Lecture #39: Problem Solving Credit: Eric Ringger

  2. A Rough-Draft Set of Questionsfor Problem Solving

  3. Problem-Solving • Problem Formulation • Algorithm Design • Algorithm Analysis • Theoretical Analysis: classify as asymptotic order of growth • Empirical Analysis • Proofs of Correctness

  4. Questions for Problem Formulation • What do I know? • What do I not know but I want to know? • What are my assumptions? • Can I formulate the problem as a graph? • Can the problem be reduced to a familiar problem? • Is the problem an optimization problem? • Is the objective linear? • Does the problem have constraints? • Are the constraints linear?

  5. Questions for Algorithm Design • Do I recognize the problem and know an algorithm that solves this problem? • Is the problem NP-Hard but not NP-Complete? • Is the problem NP-complete? • Is it in NP? • Can I reduce a known NP-complete problem to it? • Does the problem decompose nicely into sub-problems? • Do the sub-problems overlap? • Does the optimality property hold?

  6. Exercise • Can you organize these questions (both problem formulation and algorithm design) into a usable decision tree to guide you in the practice of problem-solving?

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