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  2. Problem solving - Wikipedia

    en.wikipedia.org/wiki/Problem_solving

    Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields. The former is an example of simple problem solving (SPS) addressing one issue ...

  3. Heuristic (computer science) - Wikipedia

    en.wikipedia.org/wiki/Heuristic_(computer_science)

    Heuristic (computer science) In mathematical optimization and computer science, heuristic (from Greek εὑρίσκω "I find, discover") is a technique designed for problem solving more quickly when classic methods are too slow for finding an exact or approximate solution, or when classic methods fail to find any exact solution in a search space.

  4. Heuristic - Wikipedia

    en.wikipedia.org/wiki/Heuristic

    A heuristic (/ h j ʊ ˈ r ɪ s t ɪ k /; from Ancient Greek εὑρίσκω (heurískō) 'to discover, method of discovery, serving to guide, reveal'), or heuristic technique, is any approach to problem solving that employs a pragmatic method that is not fully optimized, perfected, or rationalized, but is nevertheless "good enough" as an approximation or attribute substitution.

  5. Multi-objective optimization - Wikipedia

    en.wikipedia.org/wiki/Multi-objective_optimization

    Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized ...

  6. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    The satisfiability problem, also called the feasibility problem, is just the problem of finding any feasible solution at all without regard to objective value. This can be regarded as the special case of mathematical optimization where the objective value is the same for every solution, and thus any solution is optimal.

  7. Backtracking - Wikipedia

    en.wikipedia.org/wiki/Backtracking

    Backtracking. Backtracking is a class of algorithms for finding solutions to some computational problems, notably constraint satisfaction problems, that incrementally builds candidates to the solutions, and abandons a candidate ("backtracks") as soon as it determines that the candidate cannot possibly be completed to a valid solution. [1]

  8. Brute-force search - Wikipedia

    en.wikipedia.org/wiki/Brute-force_search

    Brute-force search. In computer science, brute-force search or exhaustive search, also known as generate and test, is a very general problem-solving technique and algorithmic paradigm that consists of systematically checking all possible candidates for whether or not each candidate satisfies the problem's statement.

  9. Reduction (complexity) - Wikipedia

    en.wikipedia.org/wiki/Reduction_(complexity)

    In computability theory and computational complexity theory, a reduction is an algorithm for transforming one problem into another problem. A sufficiently efficient reduction from one problem to another may be used to show that the second problem is at least as difficult as the first. Intuitively, problem A is reducible to problem B, if an ...