COMPARISON ANALYSIS FOR THE MACHINE SCHEDULING USING CROW SEARCH ALGORITHM (CSA) AND PSO

Machine Scheduling for the flexible job-shop is very important in both fields of production management and combinatorial optimization. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. For solving these issues we have adopted a new scheme called Crow Search Algorithm (CSA) here. In this paper we compared results Crow Search Algorithm (CSA) and particle Swarm Optimization (PSO) Algorithm for scheduling Problems for Single Machine Process has been taken into considerations. The evaluated results of different numbers of jobs and machine number has been tested with the schemes Crow Search Algorithm and Particle Swarm Optimization and CSA is found to be best in terms of Execution time and Global best Value. The system has been simulated in MATLAB R8 environment and with intel core i3 Processor