Application of Dragonfly Algorithm for Multi Objective Scheduling Problems in FMS

Scheduling plays an important role in Flexible Manufacturing System (FMS). Various Evolutionary Algorithms are used by different researchers to solve the multi objective scheduling problems. However, solutions obtained by some of these algorithms suffer from various issues such as struck in local optima, not support deadline constraint, poor convergence speed etc., of the FMS. In this paper, a new optimization technique called Dragonfly Algorithm (DA) is implemented for optimum scheduling of Multi objective Scheduling problems considered from the literature. The main inspiration of the DA algorithm originates from the static and dynamic swarming behaviors of dragonfly in nature. The Combined Objective Function (COF) is formulated by considering two objectives such as Minimization of machine idle time and Penalty cost minimization with equal weight-ages. MATLAB code has developed to determine the COF values and also for implementing Dragonfly Algorithm to obtain the optimum solution. It is observed that, the results obtained by DA algorithm are very competitive when compared with other well-known algorithms like Genetic Algorithm, Particle Swarm Optimization, Cuckoo Search, Modified Cuckoo Search & Jaya Algorithms.