Title :
An integrated framework for devising optimum generation schedules
Author :
Srinivasan, Dipti ; Tettamanzi, Andrea G B
fDate :
Nov. 29 1995-Dec. 1 1995
Abstract :
An integrated framework for generating optimum unit commitment and dispatch schedules is presented in this paper. The work reported here employs a hybrid technique by which a genetic population can be confined to a set of feasible solutions. Heuristics are used to ensure that all the constraints, both linear and nonlinear, are fulfilled for each member of the population. The use of this technique, which combines the advantages of knowledge-based methods with the strengths of evolutionary algorithms, results in considerable reduction in computing time, making its application viable in daily operation scheduling
Keywords :
Constraint optimization; Costs; Evolutionary computation; Genetic algorithms; Job shop scheduling; Lagrangian functions; Optimal scheduling; Power generation; Processor scheduling; Simulated annealing;
Conference_Titel :
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location :
Perth, WA, Australia
Print_ISBN :
0-7803-2759-4
DOI :
10.1109/ICEC.1995.489109