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In this code, quantum particle swarm optimization (QPSO) is utilized to solve multiobjective combined economic emission dispatch (CEED) problem formulated using cubic criterion function considering a uni wise max/max price penalty factor. QPSO is implemented on a 6-unit power generation system and compared with Lagrangian relaxation, particle swarm optimization (PSO) and simulated annealing (SA). The obtained results verified the effectiveness and demonstrate the robustness of QPSO method. This research suggests that QPSO can be used as an effective and robust tool in other power dispatch problems.
Cite As
Fahad Mahdi (2026). Quantum Particle Swarm Optimization for Multi-objective Combined Economic Emission Dispatch Problem (https://www.mathworks.com/matlabcentral/fileexchange/64896-quantum-particle-swarm-optimization-for-multi-objective-combined-economic-emission-dispatch-problem), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0.0 (3.6 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
