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  2. Knapsack problem - Wikipedia

    en.wikipedia.org/wiki/Knapsack_problem

    This restriction then means that an algorithm can find a solution in polynomial time that is correct within a factor of (1-ε) of the optimal solution. [26] algorithm FPTAS is input: ε ∈ (0,1] a list A of n items, specified by their values, , and weights output: S' the FPTAS solution P := max {} // the highest item value K := ε for i from 1 ...

  3. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    If n is a small fixed number, then an exhaustive search for the solution is practical. L - the precision of the problem, stated as the number of binary place values that it takes to state the problem. If L is a small fixed number, then there are dynamic programming algorithms that can solve it exactly. As both n and L grow large, SSP is NP-hard.

  4. Dining philosophers problem - Wikipedia

    en.wikipedia.org/wiki/Dining_philosophers_problem

    In computer science, the dining philosophers problem is an example problem often used in concurrent algorithm design to illustrate synchronization issues and techniques for resolving them. It was originally formulated in 1965 by Edsger Dijkstra as a student exam exercise, presented in terms of computers competing for access to tape drive ...

  5. Maximum flow problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_flow_problem

    The algorithm is a variant of the push-relabel algorithm by introducing the weighted variant. The paper establishes a weight function on directed and acyclic graphs (DAG), and attempts to imitate it on general graphs using directed expander hierarchies, which induce a natural vertex ordering that produces the weight function similar to that of ...

  6. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    Various branch-and-bound algorithms, which can be used to process TSPs containing thousands of cities. Solution of a TSP with 7 cities using a simple Branch and bound algorithm. Note: The number of permutations is much less than Brute force search. Progressive improvement algorithms, which use techniques reminiscent of linear programming. This ...

  7. Local search (optimization) - Wikipedia

    en.wikipedia.org/wiki/Local_search_(optimization)

    But a solution can also be a path, and being a cycle is part of the target. A local search algorithm starts from a candidate solution and then iteratively moves to a neighboring solution; a neighborhood being the set of all potential solutions that differ from the current solution by the minimal possible extent. This requires a neighborhood ...

  8. Parsons problem - Wikipedia

    en.wikipedia.org/wiki/Parsons_problem

    Parsons problems consist of a partially completed solution and a selection of lines of code that some of which, when arranged appropriately, correctly complete the solution. There is great flexibility in how Parsons problems can be designed, including the types of code fragments from which to select, and how much structure of the solution is ...

  9. Eight queens puzzle - Wikipedia

    en.wikipedia.org/wiki/Eight_queens_puzzle

    This very poor algorithm will, among other things, produce the same results over and over again in all the different permutations of the assignments of the eight queens, as well as repeating the same computations over and over again for the different sub-sets of each solution. A better brute-force algorithm places a single queen on each row ...