An Application Genetic Algorithms for Dynamic Order Volume with Randomly and Inconsecutively Demandsv
This research presents a case study of the application of the genetic algorithm model to determine the economic
order quantity with time varying demand and lead time  in the manufacturing and retailing plastic products. The
objective is to reduce the total economic ordering cost and establish the new ordering policy. The preliminary analysis of the
inventory management of case study illustrated main problems, which was high total economic ordering cost of 73,838,600
baht according to the flat rate of the current ordering policy at 56,400 kg/month. However, it was no problem associated
with the holding cost. The further in-depth implementation had applied the genetic algorithm model. The process began with
the selection of raw materials, data collection, data analysis, model application, comparison of operating results and
performance summary. The results showed that the genetic algorithm can be used as a tool for finding the right answer of the
dynamic order volume with randomly inconsecutively demands and the lead time constant. The economic ordering cost was
decreased to 26,737,990.88 baht or 36.21%. The number of purchasing period was reduced by 5 times or 45.45%. However,
this affected the purchasing cost, which was increased to 1,692,000 baht, or 4.55%.
Keywords - Dynamic Order Volume, Integer Linear Programming, Genetic Algorithm.