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  2. Branch and bound - Wikipedia

    en.wikipedia.org/wiki/Branch_and_bound

    The following is the skeleton of a generic branch and bound algorithm for minimizing an arbitrary objective function f. [3] To obtain an actual algorithm from this, one requires a bounding function bound, that computes lower bounds of f on nodes of the search tree, as well as a problem-specific branching rule.

  3. Branch and cut - Wikipedia

    en.wikipedia.org/wiki/Branch_and_cut

    Branch and cut [1] is a method of combinatorial optimization for solving integer linear programs (ILPs), that is, linear programming (LP) problems where some or all the unknowns are restricted to integer values. [2] Branch and cut involves running a branch and bound algorithm and using cutting planes to tighten

  4. Branch and price - Wikipedia

    en.wikipedia.org/wiki/Branch_and_price

    Branch and price is a branch and bound method in which at each node of the search tree, columns may be added to the linear programming relaxation (LP relaxation). At the start of the algorithm, sets of columns are excluded from the LP relaxation in order to reduce the computational and memory requirements and then columns are added back to the LP relaxation as needed.

  5. COIN-OR - Wikipedia

    en.wikipedia.org/wiki/COIN-OR

    COIN-OR LP (CLP or Clp) is an open-source linear programming solver written in C++. It is published under the Common Public License so it can be used in proprietary software with none of the restrictions of the GNU General Public License. CLP is primarily meant to be used as a callable library, although a stand-alone executable version can be ...

  6. Cutting stock problem - Wikipedia

    en.wikipedia.org/wiki/Cutting_stock_problem

    A simple lower bound is obtained by dividing the total amount of product by the size of each master roll. The total product required is 1380 x 22 + 1520 x 25 + ... + 2200 x 20 = 407160 mm. Each master roll is 5600 mm, requiring a minimum of 72.7 rolls, which means 73 rolls or more are required.

  7. Free variables and bound variables - Wikipedia

    en.wikipedia.org/wiki/Free_variables_and_bound...

    In the lambda calculus, x is a bound variable in the term M = λx. T and a free variable in the term T. We say x is bound in M and free in T. If T contains a subterm λx. U then x is rebound in this term. This nested, inner binding of x is said to "shadow" the outer binding. Occurrences of x in U are free occurrences of the new x. [3]

  8. LimeWire Is Making a Comeback to Sell Music NFTs - AOL

    www.aol.com/finance/limewire-making-comeback...

    LimeWire is coming back to life as a digital collectibles marketplace, and it's starting with a partnership with Universal Music Group, according to a press release issued by UMG. POLL: Do You ...

  9. Maximum satisfiability problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_satisfiability_problem

    For each clause c in C, let S + c and S − c denote the sets of variables which are not negated in c, and those that are negated in c, respectively. The variables y x of the ILP will correspond to the variables of the formula F, whereas the variables z c will correspond to the clauses. The ILP is as follows:

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