Result 1 to 20 of 43 total
Heuristic solutions to the long-term unit commitment problem with cogeneration plants. (English)
Comput. Oper. Res. 39, No. 2, 269-282 (2012).
1
A binary-real-coded differential evolution for unit commitment problem: a preliminary study. (English)
Sombattheera, Chattrakul (ed.) et al., Multi-disciplinary trends in artificial intelligence. 5th international workshop, MIWAI 2011, Hyderabad, India, December 7‒9, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-25724-7/pbk). Lecture Notes in Computer Science 7080. Lecture Notes in Artificial Intelligence, 406-417 (2011).
2
Unit commitment problem using enhanced particle swarm optimization algorithm. (English)
Soft Comput. 15, No. 1, 139-148 (2011).
3
Experimental comparison of selection hyper-heuristics for the short-term electrical power generation scheduling problem. (English)
Di Chio, Cecilia (ed.) et al., Applications of evolutionary computation. EvoApplications 2011: EvoCOMNET, EvoFIN, EvoHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOG, Torino, Italy, April 27‒29, 2011. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-20519-4/pbk). Lecture Notes in Computer Science 6625, 444-453 (2011).
4
A biased random key genetic algorithm approach for unit commitment problem. (English)
Pardalos, Panos M. (ed.) et al., Experimental algorithms. 10th international symposium, SEA 2011, Kolimpari, Chania, Crete, Greece, May 5‒7, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-20661-0/pbk). Lecture Notes in Computer Science 6630, 327-339 (2011).
5
Optimizing financial and physical assets with chance-constrained programming in the electrical industry. (English)
Optim. Eng. 12, No. 1-2, 237-255 (2011).
6
Hydro-thermal commitment scheduling by tabu search method with cooling-banking constraints. (English)
Panigrahi, Bijaya Ketan (ed.) et al., Swarm, evolutionary, and memetic computing. First international conference on swarm, evolutionary, and memetic computing, SEMCCO 2010, Chennai, India, December 16‒18, 2010. Proceedings. Berlin: Springer (ISBN 978-3-642-17562-6/pbk). Lecture Notes in Computer Science 6466, 739-752 (2010).
7
An improved differential evolution scheme for the solution of large-scale unit commitment problems. (English)
Informatica, Vilnius 21, No. 2, 175-190 (2010).
8
Multi-area hydrothermal coordination using modified mixed integer hybrid differential evolution. (English)
Int. J. Bio-Inspired Comput. 2, No. 3-4, 205-212 (2010).
9
A hyper-heuristic approach for the unit commitment problem. (English)
Di Chio, Cecilia (ed.) et al., Applications of evolutionary computation. EvoApplications 2010: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoMUSART, and EvoTRANSLOG, Istanbul, Tur\-key, April 7‒9, 2010. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-12241-5/pbk). Lecture Notes in Computer Science 6025, 121-130 (2010).
10
Power generation scheduling algorithm using dynamic programming. (English)
Nonlinear Anal., Theory Methods Appl., Ser. A, Theory Methods 71, No. 12, e-Suppl., e641-e650 (2009).
11
An improved binary particle swarm optimization for unit commitment problem. (English)
Expert Syst. Appl. 36, No. 4, 8049-8055 (2009).
12
Unit commitment scheduling using binary differential evolution algorithm. (English)
Opsearch 46, No. 1, 108-122 (2009).
13
Fuzzy based fast dynamic programming solution of unit commitment with ramp constraints. (English)
Expert Syst. 26, No. 4, 307-319 (2009).
14
A computational comparison of reformulations of the perspective relaxation: SOCP vs. cutting planes. (English)
Oper. Res. Lett. 37, No. 3, 206-210 (2009).
15
Dynamic double-population particle swarm optimization algorithm for power system unit commitment. (Chinese)
J. Comput. Appl. 28, No. 1, 104-107 (2008).
16
Cost-benefit analysis and MILP for optimal reserve capacity determination in power system. (English)
Appl. Math. Comput. 196, No. 2, 752-761 (2008).
17
Monte Carlo simulation and transmission loss evaluation with probabilistic method. (Chinese)
Proc. CSEE 27, No. 34, 39-45 (2007).
18
Optimal unit commitment decision with risk assessment using tabu search. (English)
J. Inf. Optim. Sci. 28, No. 6, 965-984 (2007).
19
A floating-point genetic algorithm for solving the unit commitment problem. (English)
Eur. J. Oper. Res. 181, No. 3, 1370-1395 (2007).
20
Result 1 to 20 of 43 total
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