The satisfiability is a decision problem that belongs toNP-complete class and has significant applications invarious areas of computer science. Several works haveproposed high-performance algorithms and solvers toexplore the space of variables and look for satisfyingassignments. Pedrycz, Succi and Shai [1] have studieda fuzzy-genetic approach which demonstrates that aformula of variables can be satisfiable by assigningBoolean variables to partial true values between 0 and1. In this paper we improve this approach by proposingan improved fuzzy-genetic algorithm to avoidundesired convergence of variables to 0.5. Thealgorithm includes a repairing function that eliminatesthe recursion and maintains a reasonable computationalconvergence and adaptable population generation.Implementation and experimental results demonstratethe enhancement of solving satisfiability problems.