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  2. Feasible region - Wikipedia

    en.wikipedia.org/wiki/Feasible_region

    A problem with five linear constraints (in blue, including the non-negativity constraints). In the absence of integer constraints the feasible set is the entire region bounded by blue, but with integer constraints it is the set of red dots. A closed feasible region of a linear programming problem with three variables is a convex polyhedron.

  3. Rubber duck debugging - Wikipedia

    en.wikipedia.org/wiki/Rubber_duck_debugging

    In software engineering, rubber duck debugging (or rubberducking) is a method of debugging code by articulating a problem in spoken or written natural language. The name is a reference to a story in the book The Pragmatic Programmer in which a programmer would carry around a rubber duck and debug their code by forcing themselves to explain it ...

  4. Answer set programming - Wikipedia

    en.wikipedia.org/wiki/Answer_set_programming

    An early example of answer set programming was the planning method proposed in 1997 by Dimopoulos, Nebel and Köhler. [3] [4] Their approach is based on the relationship between plans and stable models. [5] In 1998 Soininen and Niemelä [6] applied what is now known as answer set programming to the problem of product configuration. [4]

  5. Basic solution (linear programming) - Wikipedia

    en.wikipedia.org/wiki/Basic_solution_(Linear...

    In linear programming, a discipline within applied mathematics, a basic solution is any solution of a linear programming problem satisfying certain specified technical conditions. For a polyhedron P {\displaystyle P} and a vector x ∗ ∈ R n {\displaystyle \mathbf {x} ^{*}\in \mathbb {R} ^{n}} , x ∗ {\displaystyle \mathbf {x} ^{*}} is a ...

  6. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    From a dynamic programming point of view, Dijkstra's algorithm for the shortest path problem is a successive approximation scheme that solves the dynamic programming functional equation for the shortest path problem by the Reaching method. [8] [9] [10] In fact, Dijkstra's explanation of the logic behind the algorithm, [11] namely Problem 2.

  7. Logic programming - Wikipedia

    en.wikipedia.org/wiki/Logic_programming

    Alternatively, different algorithms can be obtained with a given problem-solving strategy by using different logical representations. [23] The two main problem-solving strategies are backward reasoning (goal reduction) and forward reasoning, also known as top-down and bottom-up reasoning, respectively.

  8. A3 problem solving - Wikipedia

    en.wikipedia.org/wiki/A3_Problem_Solving

    A3 problem solving is a structured problem-solving and continuous-improvement approach, first employed at Toyota and typically used by lean manufacturing practitioners. [1] It provides a simple and strict procedure that guides problem solving by workers. The approach typically uses a single sheet of ISO A3-size

  9. Coding best practices - Wikipedia

    en.wikipedia.org/wiki/Coding_best_practices

    Understanding the problem and associated programming requirements is necessary for choosing the language best suited for the solution." [ 17 ] From Meek & Heath: "The essence of the art of choosing a language is to start with the problem, decide what its requirements are, and their relative importance since it will probably be impossible to ...

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