Integer and combinatorial optimization
Integer and combinatorial optimization
A new algorithm for the 0-1 knapsack problem
Management Science
Input models for synthetic optimization problems
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
A Genetic Algorithm for the Multidimensional Knapsack Problem
Journal of Heuristics
Experimental Evaluation of Heuristic Optimization Algorithms: A Tutorial
Journal of Heuristics
Core Problems in Knapsack Algorithms
Operations Research
Computationally Manageable Combinatorial Auctions
Computationally Manageable Combinatorial Auctions
Combinatorial Auctions: A Survey
INFORMS Journal on Computing
Synthetic Optimization Problem Generation: Show Us the Correlations!
INFORMS Journal on Computing
The core concept for the multidimensional knapsack problem
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Computers and Operations Research
Solving multidimensional 0---1 knapsack problem with an artificial fish swarm algorithm
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
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This paper introduces new problem-size reduction heuristics for the multidimensional knapsack problem. These heuristics are based on solving a relaxed version of the problem, using the dual variables to formulate a Lagrangian relaxation of the original problem, and then solving an estimated core problem to achieve a heuristic solution to the original problem. We demonstrate the performance of these heuristics as compared to legacy heuristics and two other problem reduction heuristics for the multi-dimensional knapsack problem. We discuss problems with existing test problems and discuss the use of an improved test problem generation approach. We use a competitive test to highlight the performance of our heuristics versus the legacy heuristic approaches. We also introduce the concept of computational versus competitive problem test data sets as a means to focus the empirical analysis of heuristic performance.