Application of metaheuristic approach in parallel flow line scheduling

A metaheuristics approach is chosen in cases where the exact methods are not enough to provide a solution. It is an iterative process to efficiently produce solutions which are closer to the global optimum.. This paper addresses the application of generic algorithm for a parallel machine flow line scheduling problem using the algorithm proposed for minimizing the makespan. Sequencing of operations to attain a feasible minimum makespan is one of the important requirements to achieve effective production from process planning. Since the problem is NP-hard, it is chosen to adopt genetic algorithm as it is one of the proven methods to search for a feasible optimal solution to the objective function. This paper addresses the methodology to obtain a near optimal sequence of jobs for an allocation of constrained resources with the objective of minimization of overall completion time or makespan. The methodology is based on creating a group of random solutions and uses the genetic operators of cross over and mutation to improve the solutions till an acceptable fitness level is reached. As the implementation of the local search is time consuming, a tool based on visual basic was developed to do the search faster. The tool had the options to search exhaustively or using the genetic algorithm methods. The computational experiments deployed indicate that it is feasible with the proposed methodology and procedures to arrive at better solutions faster than the conventional methods.