A generalization of Polyak's convergence result for subgradient optimization
Mathematical Programming: Series A and B
Convergence of a generalized subgradient method for nondifferentiable convex optimization
Mathematical Programming: Series A and B
An efficient preprocessing procedure for the multidimensional 0–1 knapsack problem
Discrete Applied Mathematics - Special volume: viewpoints on optimization
A Genetic Algorithm for the Multidimensional Knapsack Problem
Journal of Heuristics
Algorithms for optimizing piecewise linear functions and for degree-constrained minimum spanning tree problems
An Exact Algorithm for the Two-Constraint 0--1 Knapsack Problem
Operations Research
Reoptimization in Lagrangian methods for the 0-1 quadratic knapsack problem
Computers and Operations Research
Shift-and-merge technique for the DP solution of the time-constrained backpacker problem
Computers and Operations Research
A theory and algorithms for combinatorial reoptimization
LATIN'12 Proceedings of the 10th Latin American international conference on Theoretical Informatics
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First, this paper deals with lagrangean heuristics for the 0-1 bidimensional knapsack problem. A projected subgradient algorithm is performed for solving a lagrangean dual of the problem, to improve the convergence of the classical subgradient algorithm. Secondly, a local search is introduced to improve the lower bound on the value of the biknapsack produced by lagrangean heuristics. Thirdly, a variable fixing phase is embedded in the process. Finally, the sequence of 0-1 one-dimensional knapsack instances obtained from the algorithm are solved by using reoptimization techniques in order to reduce the total computational time effort. Computational results are presented.