Control algorithms for optimal derivation strategy with fuzzy reasoning in knowledge-based systems are presented. Optimal derivation strategy is established in terms of antecedent-consequent relationship between a given initial state to a given goal state. The optimal strategy leads to the highest fuzzy value to the goal state. One algorithm is based on dynamic programming principle employed in a branch-and-bound paradigm. Other one employs a shortest-path framework in a fuzzy environment. The dynamic behaviour of the rule-based system is represented by fuzzy production rules. The states of the system are assumed to be represented by fuzzy linguistic expressions. The antecedent-consequent relationship of states in the system is determined bymodus ponenin fuzzy environment. The performance of the proposed algorithms is illustrated with an example.