Optimization of automotive goods preparation pattern for export using algorithm genetics

Abstract

Abstract In the case of delivery of goods for export purposes with large box dimension variations, the arrangement of goods in the fleet becomes very important as it affects the efficiencies of the cost. This situation is felt by all industrial sectors, one of which is the automotive industry. One problem is due to loading container issues, which in this case is due to the use of fleets for unfilled shipping. This is due to the fact that the delivery pattern of goods within the shipping ship is still not optimal. One solution is to optimize the space and layout of the items in the fleet. Genetic algorithm is a method of solving solutions that can be used to solve container loading problems with non-linear and heterogeneous data items, inspired by the theory of evolution. Genetic algorithm can provide optimization solutions for item preparation patterns that practice natural selection methods to get selected individuals that contain the best genes. Then the data will be repeated for several generations and yield the best array pattern output or achieve the target, in this case the minimum free space.