Abstract
This study proposes a new hybrid heuristic approach that combines the quantum particle swarm optimization (QPSO) technique with a local search phase to solve the binary generalized knapsack sharing problem (GKSP). The approach also incorporates a heuristic repair operator that uses problem-specific knowledge instead of the penalty function technique commonly used for constrained problems. This study is the first to report on the application of the QPSO method to the GKSP. The efficiency of our proposed approach was tested on a large set of instances, and the results were compared to those produced by the commercial mixed integer programming solver CPLEX 12.5 of IBM-ILOG. The Experimental results demonstrated the good performance of the QPSO in solving the GKSP.
| Original language | English |
|---|---|
| Pages (from-to) | 153-164 |
| Number of pages | 12 |
| Journal | Natural Computing |
| Volume | 15 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Mar 2016 |
| Externally published | Yes |
Keywords
- Discrete optimization
- Hybrid heuristic
- Knapsack
- Max–min optimization
- Population-based heuristic