Production Optimization Design in Supply Chain Crude Palm Oil with Genetic Algorithm Method

Abstract

Indonesia is the world's largest producer of crude palm oil (CPO). At peak harvest conditions, frequent accumulation of fresh fruit bunches (FFB) due to abundant raw materials. Based on data from one palm oil mill in the province of North Sumatra, the percentage of FFB stays in the field overnight, which is 41% of the total FFB though, on the one hand FFB that has been harvested must be processed immediately because it can affect the quality of oil to be produced. Besides that, the factors of production and storage processes are also very influential on the quality of CPO. The imbalance in production planning shows that production planning is not yet optimal in the CPO supply chain so that a production optimization design is needed in the CPO supply chain. The genetic algorithm was chosen in the completion of the optimization model because of the complex characteristics of the CPO supply chain. The purpose of this research is to optimize the palm oil supply chain system to minimize production costs. This method shows that the optimum production yield for the third quarter of 2017 is 12,202,285 kg. With the proposed system an increase in the percentage of CPO production was obtained by 8.34% compared to the actual system.