Production Scheduling for Flexible Flowshop using Genetic Algorithms

This paper was to study the production scheduling for the industry enabling to change the product form according to customer's order. From a variety of products lengthened the process steps and time. The paper studied how to schedule the production table for increasing the efficiency of flexible flow system scheduling. The two state units were experimented. Each unit consisted of unrelated parallel machines. Then, based on the customer's needs, the flexible flow system production tables were scheduled with the genetic method. The experiment with data characterized by a normal distribution as the number of 20, 50, 80 and 107 jobs was implemented. The results showed that the production scheduling with the genetic method enabled to reduce the production time from 14 days into 12.4 days, or 11.42 percent, and the time analysis of the program processing had the significant relation to the number of the jobs, and the number of the search model.