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  2. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    Linear programming (LP), also called linear optimization, is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements and objective are represented by linear relationships. Linear programming is a special case of mathematical programming (also known as mathematical optimization).

  3. Design optimization - Wikipedia

    en.wikipedia.org/wiki/Design_optimization

    Design optimization applies the methods of mathematical optimization to design problem formulations and it is sometimes used interchangeably with the term engineering optimization. When the objective function f is a vector rather than a scalar, the problem becomes a multi-objective optimization one.

  4. Assignment problem - Wikipedia

    en.wikipedia.org/wiki/Assignment_problem

    Worked example of assigning tasks to an unequal number of workers using the Hungarian method. The assignment problem is a fundamental combinatorial optimization problem. In its most general form, the problem is as follows: The problem instance has a number of agents and a number of tasks.

  5. Branch and cut - Wikipedia

    en.wikipedia.org/wiki/Branch_and_cut

    This description assumes the ILP is a maximization problem.. The method solves the linear program without the integer constraint using the regular simplex algorithm.When an optimal solution is obtained, and this solution has a non-integer value for a variable that is supposed to be integer, a cutting plane algorithm may be used to find further linear constraints which are satisfied by all ...

  6. Fundamental theorem of linear programming - Wikipedia

    en.wikipedia.org/wiki/Fundamental_theorem_of...

    In mathematical optimization, the fundamental theorem of linear programming states, in a weak formulation, that the maxima and minima of a linear function over a convex polygonal region occur at the region's corners.

  7. Basic feasible solution - Wikipedia

    en.wikipedia.org/wiki/Basic_feasible_solution

    In the theory of linear programming, a basic feasible solution (BFS) is a solution with a minimal set of non-zero variables. Geometrically, each BFS corresponds to a vertex of the polyhedron of feasible solutions. If there exists an optimal solution, then there exists an optimal BFS.

  8. Linear programming relaxation - Wikipedia

    en.wikipedia.org/wiki/Linear_programming_relaxation

    The process begins by considering a subproblem in which no variable values have been assigned, and in which V 0 is the whole set of variables of the original problem. Then, for each subproblem i, it performs the following steps. Compute the optimal solution to the linear programming relaxation of the current subproblem.

  9. Cutting stock problem - Wikipedia

    en.wikipedia.org/wiki/Cutting_stock_problem

    Metallised film (used in packaging of snacks), and plastic extrusion on paper (used in liquid packaging, e.g. juice cartons) are further examples of such a process. Winder constraints where the slitting process has physical or logical constraints: a very common constraint is that only a certain number of slitting knives are available, so that ...