A Study on the optimization of Multi-cycle and Multi-source Procurement and Transport of Enterprises Based on the Genetic Algorithm

Enterprises put forward higher requirements on selection of raw material suppliers and forwarders, while minimizing product costs in real production. Aiming at optimization of multi-source and multi-cycle suppliers and forwarders, we established an evaluation system first by selecting evaluation indicators with the multiple link relatives method and the TOPSIS method; then built a multi-objective optimization model for selection of suppliers and forwarders with consideration of the transport loss rate, based on the objectives of the most economical cost of raw materials and the least transport loss, under the premise that the stock can support normal production; optimized and improved the sifting operator of the genetic algorithm; and analyzed the effect and feasibility of the implementation.