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  2. Tabu search - Wikipedia

    en.wikipedia.org/wiki/Tabu_search

    Tabu search is a metaheuristic algorithm that can be used for solving combinatorial optimization problems (problems where an optimal ordering and selection of options is desired). Current applications of TS span the areas of resource planning, telecommunications, VLSI design, financial analysis, scheduling, space planning, energy distribution ...

  3. Set packing - Wikipedia

    en.wikipedia.org/wiki/Set_packing

    Set packing. Set packing is a classical NP-complete problem in computational complexity theory and combinatorics, and was one of Karp's 21 NP-complete problems. Suppose one has a finite set S and a list of subsets of S. Then, the set packing problem asks if some k subsets in the list are pairwise disjoint (in other words, no two of them share ...

  4. Bin packing problem - Wikipedia

    en.wikipedia.org/wiki/Bin_packing_problem

    Despite its worst-case hardness, optimal solutions to very large instances of the problem can be produced with sophisticated algorithms. In addition, many approximation algorithms exist. For example, the first fit algorithm provides a fast but often non-optimal solution, involving placing each item into the first bin in which it will fit.

  5. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Constraint satisfaction. In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. [1] A solution is therefore an assignment of values to the variables that satisfies all constraints—that is, a point in ...

  6. Probably approximately correct learning - Wikipedia

    en.wikipedia.org/wiki/Probably_approximately...

    In computational learning theory, probably approximately correct ( PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant. [1] In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions.

  7. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    The subset sum problem (SSP) is a decision problem in computer science. In its most general formulation, there is a multiset of integers and a target-sum , and the question is to decide whether any subset of the integers sum to precisely . [1] The problem is known to be NP-complete. Moreover, some restricted variants of it are NP-complete too ...

  8. Solution set - Wikipedia

    en.wikipedia.org/wiki/Solution_set

    Solution set. In mathematics, a solution set is the set of values that satisfy a given set of equations or inequalities . For example, for a set of polynomials over a ring , the solution set is the subset of on which the polynomials all vanish (evaluate to 0), formally. The feasible region of a constrained optimization problem is the solution ...

  9. Iterative deepening A* - Wikipedia

    en.wikipedia.org/wiki/Iterative_deepening_A*

    Iterative deepening A* ( IDA*) is a graph traversal and path search algorithm that can find the shortest path between a designated start node and any member of a set of goal nodes in a weighted graph. It is a variant of iterative deepening depth-first search that borrows the idea to use a heuristic function to conservatively estimate the ...