Research of Electric Power Industry's Production Logistics Model Based on Hybrid Chaos Immune Evolutionary Optimization Algorithm

Abstract

Inventory control is an important aspect of production logistics management in power system. According to the characteristic of raw material purchase and stock, the paper puts forward an optimal inventory model to minimize the cost. A novel hybrid chaos immune evolutionary optimization algorithm (HCIEOA) of solving the minimal purchasing cost problem is presented. This algorithm integrates space-searching advantages of the chaos optimization algorithm (COA) and immune evolutionary algorithm (IEA). It uses the ergodic property of the chaos system to overcome redundancies, and uses the chaos initial sensitivity to enlarge the searching space. Thus, the diversity of population is retained, the local optimization is avoided, and the rapidity of global optimization is improved. Then, this model is applied to the process of searching the optimization in the purchase and storage model. At last, the example shows that the HCIEOA is effective and reliable.