Scheduling is one of the most important problems in any manufacturing industry.
Therefore, the problem has been studied extendedly. Since, the scheduling problem is classified
as NP-hard problem, which means the time required for finding the optimal solution of the
problem is grown exponentially with the size of the problem. Therefore, it is unrealistic to find
optimal solution for the scheduling problem in the scene of the real world industrial case, even
with today advanced computer system.
There are many heuristic algorithms have been proposal to solve the scheduling problem.
They are beam search, local search technique, tabular search and Genetic Algorithm (GA), to
name a few. In recent years, GA has become a noticeable candidate for solving the scheduling
problem effectively. The idea of mimicking the evolutionary process is very interesting to
researchers. And the recent advanced in heuristic GA has sparked more attention toward new
research and application in the field of GA.
In Brewery industry, the fermentation process is the most crucial components of the whole
manufacturing process. It will decide the quality, taste of the products as well as the
productivity of the production line. Since, the fermentation time can take up to 41 days, and the
requirement time is varying a lot between different types of beers, therefore finding a good
scheduling solution to dealing with this complexity is crucial for beer manufacturers. This
research will propose a GA to solve the scheduling problem in beer production. The proposed
methodology will serve as a planning and analysis tool to utilize assets (tanks, filling lines)
effectively, reduce congestion and synchronize the production process between the two
production stages (liquid preparation and bottling).
Keywords: scheduling, lot sizing, brewery industry, two-stage production, GA.