Research on Logistics Distribution Vehicle Scheduling Based on Heuristic Genetic Algorithm

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 s...

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Published inComplexity (New York, N.Y.) Vol. 2021; no. 1
Main Authors Wang, Chun-Li, Wang, Yang, Zeng, Ze-Yu, Lin, Cheng-Yu, Yu, Qiu-Li
Format Journal Article
LanguageEnglish
Published Hoboken Hindawi 30.08.2021
John Wiley & Sons, Inc
Wiley
Subjects
Online AccessGet full text
ISSN1076-2787
1099-0526
1099-0526
DOI10.1155/2021/8275714

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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.
AbstractList 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.
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.
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.
Audience Academic
Author Wang, Yang
Wang, Chun-Li
Yu, Qiu-Li
Zeng, Ze-Yu
Lin, Cheng-Yu
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Copyright © 2021 Chun-Li Wang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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Snippet 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...
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...
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...
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SubjectTerms Algorithms
Carts
Control stability
Cost control
Efficiency
Genetic algorithms
Genetic research
Internet of Things
Logistics
Mathematical analysis
Mutation
Optimization
Optimization algorithms
Picking
Population
Scheduling
Traveling salesman problem
Warehouses
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Title Research on Logistics Distribution Vehicle Scheduling Based on Heuristic Genetic Algorithm
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