Research on IRP of Perishable Products Based on Improved Differential Evolution Algorithm

Abstract

Inventory routing problem is a NP-hard problem, and its research has always been a hot issue. The special operation of perishable goods puts forward higher requirements for inventory and transportation. In order to reduce the quantity of deteriorated goods, improve the storage efficiency of perishable goods, and further reduce the operating cost of enterprises, the inventory path problem is studied on the basis of inventory path problem. In order to rationally arrange the distribution time, quantity and route of each customer point, a mathematical model is established on the basis of some assumptions, taking inventory and vehicles as constraints, and aiming at optimizing the total cost of the system. In view of the particularity of perishable goods inventory routing problem, the proposed algorithm (IDE) improves the differential evolution algorithm from two perspectives. The grid is used to initialize the population and the greedy local optimization algorithm is combined with the differential evolution algorithm to improve the convergence speed of the algorithm. The accuracy of the algorithm is improved by adaptive scaling factor, two evolutionary modes and changing the constraints of the problem. Then the improved algorithm is used to solve the inventory routing problem. The numerical results show that the algorithm is effective and feasible, and can improve the accuracy of the algorithm and accelerate the convergence speed of the algorithm.