  This paper presents a new algorithm based on integrating Genetic Algorithms
and Tabu Search methods to solve the Job Shop Scheduling problem. The idea of
the proposed algorithm is derived from Genetic Algorithms. Most of the
scheduling problems require either exponential time or space to generate an
optimal answer. Job Shop scheduling (JSS) is the general scheduling problem and
it is a NP-complete problem, but it is difficult to find the optimal solution.
This paper applies Genetic Algorithms and Tabu Search for Job Shop Scheduling
problem and compares the results obtained by each. With the implementation of
our approach the JSS problems reaches optimal solution and minimize the
makespan.
