Application of Modified Steady-State Genetic Algorithm for Batch Sizing and Scheduling Problem with Limited Buffers

Batch sizing and scheduling problems are usually tough to solve because they seek solutions in a vast combinatorial space of possible solutions. This research aimed test further develop method based on modified steady-state genetic algorithm its performance, both the speed (low computational time) quality final results as low makespan values. paper explores problem determining order size product batches hybrid flow shop with limited buffer according that is faced real-life. Another goal this was new reliable software/computer program tool c# can also be used production, result, obtain flexible software solution for research. In all optimizations, initial population randomly generated. The obtained results, short computation time, together flexibility paradigm prove effectiveness proposed problem.