Research on Logistics Distribution Vehicle Scheduling Based on Heuristic Genetic Algorithm

Chun-Li Wang,Yang Wang,Cheng-Yu Lin,Qiu-Li Yu,Ze-Yu Zeng,Muhammad Javaid

doi:10.1155/2021/8275714

Abstract

To study the genetic algorithm, this paper solves the problem of shop scheduling under the premise of layout Flying − V . Firstly, double-layer coding is used for optimization. When calculating fitness, the time to return to the mouth P & D approaches the optimum through the greedy idea. Individual screening is carried out through the roulette method. Different crossover and genetic operators are used for different coding layers. Through thinking of elitism and catastrophe and the immigration operator to ensure the diversity of the algorithm in the calculation process, it can achieve the recommendation of the number of cars to control the cost. The stability of the algorithm is good. It can recommend a better picking sequence and number of carts for various types of picking problems.

Highlights

In recent years, Germany has proposed the “Industry 4.0” project, which uses the Internet of things information system to digitalize and intelligentize supply, manufacturing, and sales information in production
Regarding the dispatching optimization plan of the cargo trolley, Venkitasubramony and Adil [17] and Le and Degui [18] (2013) constructed a warehouse location allocation model based on layout Fishbone, used a hybrid algorithm combining genetic algorithm and ant colony algorithm, and improved layout Fishbone methods to optimize the allocation of many locations. e model is solved, combined with warehouse examples, to find the best warehouse layout
E topic will be based on the layout optimization; at the same time, through the genetic algorithm, the recommendation of the number of picking carts and the recommendation of the route can solve the problem of improving the circulation efficiency of warehousing logistics and reducing the circulation fee [22]

Summary

Introduction

Germany has proposed the “Industry 4.0” project, which uses the Internet of things information system to digitalize and intelligentize supply, manufacturing, and sales information in production. Regarding the dispatching optimization plan of the cargo trolley, Venkitasubramony and Adil [17] and Le and Degui [18] (2013) constructed a warehouse location allocation model based on layout Fishbone, used a hybrid algorithm combining genetic algorithm and ant colony algorithm, and improved layout Fishbone methods to optimize the allocation of many locations. E topic will be based on the layout optimization; at the same time, through the genetic algorithm, the recommendation of the number of picking carts and the recommendation of the route can solve the problem of improving the circulation efficiency of warehousing logistics and reducing the circulation fee [22]. 2w􏼌􏼌􏼌􏼌􏼌xi − xj􏼌􏼌􏼌􏼌􏼌􏼓k, yi + yj, d2􏼒􏼌􏼌􏼌􏼌􏼌xi − xj + 1􏼌􏼌􏼌􏼌􏼌􏼓, Dis(i, 0) + Dis(j, 0),

Genetic Algorithm to Solve the Problem

3.11. Algorithm Structure

Conclusion