An Efficient Hybrid Algorithm for the Separable Convex Quadratic Knapsack Problem

Timothy A. Davis, William W. Hager, James T. Hungerford
2016 ACM Transactions on Mathematical Software  
This paper considers the problem of minimizing a convex, separable quadratic function subject to a knapsack constraint and a box constraint. An algorithm called NAPHEAP is developed for solving this problem. The algorithm solves the Karush-Kuhn-Tucker system using a starting guess to the optimal Lagrange multiplier and updating the guess monotonically in the direction of the solution. The starting guess is computed using the variable fixing method or is supplied by the user. A key innovation in
more » ... our algorithm is the implementation of a heap data structure for storing the break points of the dual function, and computing the solution of the dual problem. Also, a new version of the variable fixing algorithm is developed that is convergent even when the objective Hessian is not strictly positive definite. The hybrid algorithm NAPHEAP that uses a Newton-type method (variable fixing method, secant method, or Newton's method) to bracket a root, followed by a heap-based monotone break point search, can be faster than a Newton-type method by itself, as demonstrated in the numerical experiments.
doi:10.1145/2828635 fatcat:mkkmbrxhxncsjlyxlkm3bfmuuy