Abstract :
In this paper, we use the genetic algorithms (GA) technique to handle two problems in the manufacturing systems: the formation of manufacturing cell in cellular manufacturing and batch scheduling. In the formation of machine cells, we use multi-objective functions as criteria to form cell. These criteria are to minimise the inter-cell movement, to minimise variation of workload within cells and to maximise the similarity within cells. Results showed that by varying the weights of each criterion, the algorithm produced is flexible to adapt to changes in the manufacturing environment. Unlike traditional methods which merely rearrange the part-incidence matrix, this algorithm incorporates other parameters such as processing times of each part and number of parts required. The batch scheduling problem described in this paper is the problem of scheduling a single-machine with jobs of different due-dates and arrival times. We have developed an algorithm which is not only able to find the optimum or near-optimal sequence of jobs, but also able to determine the number of jobs to be processed in each batch. The objective function used is to minimise total tardiness.
