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    A Branch and Bound Algorithm for Solving a Capacitated Subtree of a Tree Problem in Local Access Telecommunication Networks

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    https://www.riss.kr/link?id=A30080426

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    Given a rooted tree T with node profits and node demands, the capacitated subtree of a tree problem(CSTP) consists of finding a rooted subtree of maximum profit, subject to having total demand no larger than the given capacity H. We first define the so-called critical item for CSTP and find an upper bound on the optimal value of CSTP in O(n^2) time, where n is the number of nodes in T. We then present our branch and bound algorithm for solving CSTP and illustrate the algorithm by using an example. Finally, we implement our branch-and-bound algorithm and compare the computational results with those for both CPLEX and a dynamic programming algorithm. The comparison shows that our branch-and-bound algorithm performs much better than both CPLEX and the dynamic programming algorithm, where n and H are in the range of [5000. 10000] respectively.
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    Given a rooted tree T with node profits and node demands, the capacitated subtree of a tree problem(CSTP) consists of finding a rooted subtree of maximum profit, subject to having total demand no larger than the given capacity H. We first define the s...

    Given a rooted tree T with node profits and node demands, the capacitated subtree of a tree problem(CSTP) consists of finding a rooted subtree of maximum profit, subject to having total demand no larger than the given capacity H. We first define the so-called critical item for CSTP and find an upper bound on the optimal value of CSTP in O(n^2) time, where n is the number of nodes in T. We then present our branch and bound algorithm for solving CSTP and illustrate the algorithm by using an example. Finally, we implement our branch-and-bound algorithm and compare the computational results with those for both CPLEX and a dynamic programming algorithm. The comparison shows that our branch-and-bound algorithm performs much better than both CPLEX and the dynamic programming algorithm, where n and H are in the range of [5000. 10000] respectively.

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