This paper presents the application of a fuzzy logic controlled genetic algorithm to environmental/economic dispatch. The paper first proposes an improved genetic algorithm with two fuzzy controllers based on some heuristics to adaptively adjust the crossover probability and mutation rate during the optimization process. The implementation of the fuzzy crossover and mutation controllers is described. The proposed FCGA can be applied to a wide range of optimization problems. The validity of the proposed algorithm is illustrated on environmental/economic dispatch of a six-generator system. Its performance is compared with conventional GA and the Newton-Raphson method. The results are very encouraging.