Scheduling Flow Line Manufacturing Cell through Multi Objective Memetic Algorithm Plánovanie priebežnej výrobnej bunky s využitím multi-účelového algoritmu Memetic

In recent years Cellular Manufacturing has become an effective tool for improving productivity. Attainment of full benefits of Cellular Manufacturing depends firstly on the design of the machine cells and part families, secondly on the method of operations which takes full advantage of cell properties. Inappropriate methods of loading and scheduling can even lead to the failure of the Cellular Manufacturing Systems (CMS), however efficiently the cell is designed. In this paper, a new meta heuristics called Memetic Algorithm (MA) is introduced to solve Scheduling problems with multi objectives in Flow Line Manufacturing Cell (FMC). The problem of job scheduling in a flow line-manufacturing cell is considered with the multiple criterions of minimizing the makespan, total flow time and total idle time. Effort has been made to develop an algorithm that is more reliable than the conventional methods and compared with some non-traditional optimization techniques like Genetic Algorithm (GA), Tabu Search Algorithm (TS) for solving flow line manufacturing cell problems. In the Memetic Algorithm approach, local search (Tabu Search) is applied to each newly generated offspring at the end of Genetic Algorithm. The hybrid approach has been developed from the concepts of Genetic Algorithm [GA] and Tabu Search [TS]. C++ programs to execute the Genetic Algorithm, Tabu Search and Memetic Algorithm have been coded. The results of an extensive computational investigation for various problem sizes are presented. It has been observed that the Memetic Algorithm approach performs better than GA and TS approaches in giving solutions of superior quality.