GAVLCRG: genetic algorithm with variable length chromosome-based rule generation scheme for fuzzy controllers. This paper presents novel technique for the design of Mamdani type fuzzy controller using Genetic Algorithm with Variable Length Chromosome based Rule Generation scheme (GAVLCRG). This scheme helps for efficient ways of sampling the search space with varying length dimensionalities and there by simultaneously optimizing the number of rules and the parameters of both antecedent and consequent linguistic terms. Moreover, evolving natural organisms from simple to ever more complex ones with associated increase of genotype length can be achieved through GAVLCRG using new operators for variable length chromosome like extended crossover, one-sided sharing, two-sided sharing, donation, gene pruning and gene removal. The new GAVLCRG scheme is applied to find out the rules (i) for identifying the function y=4(x-0·5) 2 . (ii) for designing Mamdani type fuzzy rules with singleton consequents for the benchmarking control problem of inverted pendulum (iii) for designing Mamdani type fuzzy rules with fuzzy consequents for the problem of inverted pendulum.