The Flexible Job Shop scheduling Problem has originated from the classical job shop scheduling problem. In FJSP an operation has the flexibility to be processed on any of the machine from a set of capable machines. Routing and scheduling are the two problems that make up the FJSP. Routing is the assigning of each operation to a machine out of a given set of eligible machines. Scheduling is the sequencing of all the assigned operations on the selected machines. The FJSP finds its importance in many research fields and can be applied to a large variety of real-world problems that can be modeled as a FJSP. They include simulation and optimization of transport systems, combinatorial optimization, scheduling in actual manufacturing systems etc. In this paper we propose an Improved Firefly algorithm to solve the FJSP. In this machine allocation and the problem of sequencing the operation are solved by developing a suitable conversion of the continuous functions. The functions such as attractiveness, distance, and movement are trans-formed into a form of new discrete functions. Different benchmark data taken from the literature are used to evaluate and compare the performance of proposed algorithm. The computational re-sults show that the developed Improved FFA gave better results than the other author's algorithm.