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  2. Mixed complementarity problem - Wikipedia

    en.wikipedia.org/wiki/Mixed_complementarity_problem

    The mixed complementarity problem is defined by a mapping ():, lower values {} and upper values {}, with {, …,}. The solution of the MCP is a vector x ∈ R n {\displaystyle x\in \mathbb {R} ^{n}} such that for each index i ∈ { 1 , … , n } {\displaystyle i\in \{1,\ldots ,n\}} one of the following alternatives holds:

  3. Bin packing problem - Wikipedia

    en.wikipedia.org/wiki/Bin_packing_problem

    In the guillotine cutting problem, both the items and the "bins" are two-dimensional rectangles rather than one-dimensional numbers, and the items have to be cut from the bin using end-to-end cuts. In the selfish bin packing problem, each item is a player who wants to minimize its cost. [53]

  4. Anderson acceleration - Wikipedia

    en.wikipedia.org/wiki/Anderson_acceleration

    In mathematics, Anderson acceleration, also called Anderson mixing, is a method for the acceleration of the convergence rate of fixed-point iterations. Introduced by Donald G. Anderson, [ 1 ] this technique can be used to find the solution to fixed point equations f ( x ) = x {\displaystyle f(x)=x} often arising in the field of computational ...

  5. Mixture distribution - Wikipedia

    en.wikipedia.org/wiki/Mixture_distribution

    In probability and statistics, a mixture distribution is the probability distribution of a random variable that is derived from a collection of other random variables as follows: first, a random variable is selected by chance from the collection according to given probabilities of selection, and then the value of the selected random variable is realized.

  6. Integer programming - Wikipedia

    en.wikipedia.org/wiki/Integer_programming

    An integer programming problem is a mathematical optimization or feasibility program in which some or all of the variables are restricted to be integers.In many settings the term refers to integer linear programming (ILP), in which the objective function and the constraints (other than the integer constraints) are linear.

  7. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    Solving an equation f(x) = g(x) is the same as finding the roots of the function h(x) = f(x) – g(x). Thus root-finding algorithms can be used to solve any equation of continuous functions. However, most root-finding algorithms do not guarantee that they will find all roots of a function, and if such an algorithm does not find any root, that ...

  8. 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.

  9. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    HiGHS has an interior point method implementation for solving LP problems, based on techniques described by Schork and Gondzio (2020). [10] It is notable for solving the Newton system iteratively by a preconditioned conjugate gradient method, rather than directly, via an LDL* decomposition. The interior point solver's performance relative to ...