Core Problems in Knapsack Algorithms
Operations Research
On Quality of Service Optimization with Discrete QoS Options
RTAS '99 Proceedings of the Fifth IEEE Real-Time Technology and Applications Symposium
Quality adaptation in a multisession multimedia system: model, algorithms, and architecture
Quality adaptation in a multisession multimedia system: model, algorithms, and architecture
Where are the hard knapsack problems?
Computers and Operations Research
A Reactive Local Search-Based Algorithm for the Multiple-Choice Multi-Dimensional Knapsack Problem
Computational Optimization and Applications
Solving the multidimensional multiple-choice knapsack problem by constructing convex hulls
Computers and Operations Research
Packing and partitioning orbitopes
Mathematical Programming: Series A and B
Query range problem in wireless sensor networks
IEEE Communications Letters
A column generation method for the multiple-choice multi-dimensional knapsack problem
Computational Optimization and Applications
MVRC heuristic for solving the multi-choice multi-constraint knapsack problem
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
A New Heuristic for Solving the Multichoice Multidimensional Knapsack Problem
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A novel multi-population genetic algorithm for multiple-choice multidimensional knapsack problems
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
Development of core to solve the multidimensional multiple-choice knapsack problem
Computers and Industrial Engineering
Computers and Operations Research
Approximation schemes for deal splitting and covering integer programs with multiplicity constraints
Theoretical Computer Science
First-level tabu search approach for solving the multiple-choice multidimensional knapsack problem
International Journal of Metaheuristics
A scalable GPU-based approach to accelerate the multiple-choice knapsack problem
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
Piece selection algorithms for layered video streaming in P2P networks
Discrete Applied Mathematics
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Recent advances in algorithms for the multidimensional multiple choice knapsack problems have enabled us to solve rather large problem instances. However, these algorithms are evaluated with very limited benchmark instances. In this study, we propose new methods to systematically generate comprehensive benchmark instances. Some instances with special correlation properties between parameters are found to be several orders of magnitude harder than those currently used for benchmarking the algorithms. Experiments on an existing exact algorithm and two generic solvers show that instances whose weights are uncorrelated with the profits are easier compared with weakly or strongly correlated cases. Instances with classes containing similar set of profits for items and with weights strongly correlated to the profits are the hardest among all instance groups investigated. These hard instances deserve further study and understanding their properties may shed light to better algorithms.