A New Hybrid Algorithm for Cold Chain Logistics Distribution Center Location Problem

Shuihai Dou,Yubo Yang,Guanyi Liu

doi:10.1109/access.2020.2990988

Abstract

According to the perishable characteristics of refrigerated food and the objective of minimizing the total cost, the mathematical optimization model of cold chain logistics distribution center location problem is established by introducing such constraints as the freshness and time window. In order to solve the problems of slow convergence and easy to fall into local optimal solution in the process of the traditional wolf colony optimization, an immune wolf colony hybrid algorithm is proposed to solve the location problem of distribution center. In this hybrid algorithm, the idea of vaccination of immune algorithm is introduced into the wolf colony algorithm. By adjusting the antibody concentration and selecting immune operator, the diversity of the wolf colony algorithm is improved, and then the search space of the solution is expanded; the convergence speed and solution accuracy of the wolf colony algorithm are improved by using immune memory cells and immune vaccine. The simulation results show that the immune wolf colony algorithm can quickly converge to the global optimal solution and optimize the location model of logistics distribution center. The algorithm has good feasibility and robustness.

Highlights

With the continuous development of society, people have a higher pursuit of the quality of daily life, especially in the aspect of the freshness of refrigerated food, which is gradually attracting more and more attention of the public
Because the Wolf colony algorithm (WCA) has the disadvantages of slow convergence speed and easy to fall into local optimal solution, this paper proposes a hybrid algorithm based on wolf colony algorithm and immune algorithm, and solves the location problem of cold chain logistics distribution center by using the hybrid colony which is called immune wolf colony algorithm (IWCA)
THE IMMUNE WOLF CONOLY ALGORITHM 1) THE DESIGN IDEA OF THE IMMUNE WOLF COLONY ALGORITHM The immune wolf colony hybrid algorithm proposed in this paper focuses on the combination of wolf colony algorithm and immune algorithm, which makes the hybrid algorithm have the advantages of immune algorithm’s excellent solving performance in combinatorial optimization and wolf colony algorithm’s fast convergence in solving problems, and avoids the disadvantages of immune algorithm’s slow convergence speed in optimization problems and wolf colony algorithm’s easy falling into local extremum

Summary

INTRODUCTION

With the continuous development of society, people have a higher pursuit of the quality of daily life, especially in the aspect of the freshness of refrigerated food, which is gradually attracting more and more attention of the public. Because the WCA has the disadvantages of slow convergence speed and easy to fall into local optimal solution, this paper proposes a hybrid algorithm based on wolf colony algorithm and immune algorithm, and solves the location problem of cold chain logistics distribution center by using the hybrid colony which is called immune wolf colony algorithm (IWCA). By analyzing the location problem of logistics distribution center, we can get the characteristic information related to the problem, and select two best antibodies which are called initial solution of the problem from the antibody group to intersect, and take the public subset as the immune vaccine.

ALGORITHM SIMULATION AND ANALYSIS

CONCLUSION