A hybrid biased random key genetic algorithm approach for the unit commitment problem
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Title
A hybrid biased random key genetic algorithm approach for the unit commitment problem
Authors
Keywords
Unit commitment, Genetic algorithms, Hybrid metaheuristics, Electrical power generation
Journal
JOURNAL OF COMBINATORIAL OPTIMIZATION
Volume 28, Issue 1, Pages 140-166
Publisher
Springer Nature
Online
2014-02-07
DOI
10.1007/s10878-014-9710-8
References
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Note: Only part of the references are listed.- A new MILP-based approach for unit commitment in power production planning
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- A Thermal Unit Commitment Approach Using an Improved Quantum Evolutionary Algorithm
- (2009) Yun-Won Jeong et al. ELECTRIC POWER COMPONENTS AND SYSTEMS
- Quantum-Inspired Evolutionary Algorithm Approach for Unit Commitment
- (2009) T.W. Lau et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- A genetic algorithm for a single product network design model with lead time and safety stock considerations
- (2008) Karthik Sourirajan et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Fuzzy and simulated annealing based dynamic programming for the unit commitment problem
- (2008) S. Patra et al. EXPERT SYSTEMS WITH APPLICATIONS
- Tighter Approximated MILP Formulations for Unit Commitment Problems
- (2008) A. Frangioni et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- A variant of the dynamic programming algorithm for unit commitment of combined heat and power systems
- (2007) Aiying Rong et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- A genetic algorithm for the resource constrained multi-project scheduling problem
- (2007) J.F. Gonçalves et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Solving unit commitment problems with general ramp constraints
- (2007) Antonio Frangioni et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
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