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  2. Linear complementarity problem - Wikipedia

    en.wikipedia.org/wiki/Linear_complementarity_problem

    If M is such that LCP(q, M) has a solution for every q, then M is a Q-matrix. If M is such that LCP(q, M) have a unique solution for every q, then M is a P-matrix. Both of these characterizations are sufficient and necessary. [4] The vector w is a slack variable, [5] and so is generally discarded after z is found. As such, the problem can also ...

  3. Optimization problem - Wikipedia

    en.wikipedia.org/wiki/Optimization_problem

    For each combinatorial optimization problem, there is a corresponding decision problem that asks whether there is a feasible solution for some particular measure m 0. For example, if there is a graph G which contains vertices u and v , an optimization problem might be "find a path from u to v that uses the fewest edges".

  4. 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.

  5. Knapsack problem - Wikipedia

    en.wikipedia.org/wiki/Knapsack_problem

    A multiple constrained problem could consider both the weight and volume of the books. (Solution: if any number of each book is available, then three yellow books and three grey books; if only the shown books are available, then all except for the green book.) The knapsack problem is the following problem in combinatorial optimization:

  6. Combinatorial optimization - Wikipedia

    en.wikipedia.org/wiki/Combinatorial_optimization

    A minimum spanning tree of a weighted planar graph.Finding a minimum spanning tree is a common problem involving combinatorial optimization. Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, [1] where the set of feasible solutions is discrete or can be reduced to a discrete set.

  7. No free lunch in search and optimization - Wikipedia

    en.wikipedia.org/wiki/No_free_lunch_in_search...

    The problem is to rapidly find a solution among candidates a, b, and c that is as good as any other, where goodness is either 0 or 1. There are eight instances ("lunch plates") fxyz of the problem, where x, y, and z indicate the goodness of a, b, and c, respectively. Procedure ("restaurant") A evaluates candidates in the order a, b, c, and B ...

  8. Lagrangian relaxation - Wikipedia

    en.wikipedia.org/wiki/Lagrangian_relaxation

    A solution to the relaxed problem is an approximate solution to the original problem, and provides useful information. The method penalizes violations of inequality constraints using a Lagrange multiplier, which imposes a cost on violations. These added costs are used instead of the strict inequality constraints in the optimization.

  9. Corner solution - Wikipedia

    en.wikipedia.org/wiki/Corner_solution

    This is a corner solution as the highest possible IC (IC 2) intersects the budget line at one of the intercepts (x-intercept). [1] In mathematics and economics, a corner solution is a special solution to an agent's maximization problem in which the quantity of one of the arguments in the maximized function is zero. In non-technical terms, a ...