This article proposes a new algorithm to solve the knapsack problem in less time, enhancing efficiency in optimization tasks.
In this article we consider the binary knapsack problem under disjoint multiple-choice constraints. We propose a two-stage algorithm based on Lagrangian relaxation. The first stage determines in polynomial time an optimal Lagrange multiplier value, which is then used within a branch-and-bound scheme to rank-order the solutions, leading to an optimal solution in a relatively low depth of search. The validity of the algorithm is established, a numerical example is included, and computational experience is described.
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