An improved flower pollination algorithm for optimization of intelligent logistics distribution center

IF 2.8 3区工程技术 Q2 ENGINEERING, MANUFACTURING Advances in Production Engineering & Management Pub Date : 2019-06-09 DOI:10.14743/APEM2019.2.320

W. Hu

{"title":"An improved flower pollination algorithm for optimization of intelligent logistics distribution center","authors":"W. Hu","doi":"10.14743/APEM2019.2.320","DOIUrl":null,"url":null,"abstract":"It is easy to fall into local optimal solution in solving the optimal location of intelligent logistics distribution center by traditional method and the result of optimization is not ideal. For this, the study puts forward an optimization method of intelligent logistics distribution center based on improved flower pollination algorithm. This method uses the logic self-mapping function to carry out chaotic disturbance to the pollen grains, so that the pollen grain set lacking the mutation mechanism has strong self-adaptability, and the convergence of the optimal solution in the later stage of the algorithm is effectively prevented. The boundary buffer factor is used to buffer the cross-boundary pollen grains adaptively so as to prevent the algorithm from the local optimization, and the convergence speed and the optimization accuracy of the algorithm can be improved obviously in processing the optimal location of intelligent logistics distribution center. The convergence of the algorithm is analyzed theoretically by using the real number coding method, and the biological model and theoretical basis of the algorithm are given. The experimental results show that the proposed method has better performance than the traditional one, and the algorithm outperforms a genetic algorithm and particle swarm algorithm. It provides a feasible solution for the intelligent logistics distribution center location strategy. It affords a good reference for improving and optimizing the internal logistics of the manufacturing system and the operational efficiency of the entire intelligent logistics system. © 2019 CPE, University of Maribor. All rights reserved.","PeriodicalId":48763,"journal":{"name":"Advances in Production Engineering & Management","volume":"24 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2019-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Production Engineering & Management","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.14743/APEM2019.2.320","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}

引用次数: 14

Abstract

It is easy to fall into local optimal solution in solving the optimal location of intelligent logistics distribution center by traditional method and the result of optimization is not ideal. For this, the study puts forward an optimization method of intelligent logistics distribution center based on improved flower pollination algorithm. This method uses the logic self-mapping function to carry out chaotic disturbance to the pollen grains, so that the pollen grain set lacking the mutation mechanism has strong self-adaptability, and the convergence of the optimal solution in the later stage of the algorithm is effectively prevented. The boundary buffer factor is used to buffer the cross-boundary pollen grains adaptively so as to prevent the algorithm from the local optimization, and the convergence speed and the optimization accuracy of the algorithm can be improved obviously in processing the optimal location of intelligent logistics distribution center. The convergence of the algorithm is analyzed theoretically by using the real number coding method, and the biological model and theoretical basis of the algorithm are given. The experimental results show that the proposed method has better performance than the traditional one, and the algorithm outperforms a genetic algorithm and particle swarm algorithm. It provides a feasible solution for the intelligent logistics distribution center location strategy. It affords a good reference for improving and optimizing the internal logistics of the manufacturing system and the operational efficiency of the entire intelligent logistics system. © 2019 CPE, University of Maribor. All rights reserved.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

一种用于智能物流配送中心优化的改进授粉算法

传统方法在求解智能物流配送中心最优选址时容易陷入局部最优解，优化结果不理想。为此，本研究提出了一种基于改进的花卉授粉算法的智能物流配送中心优化方法。该方法利用逻辑自映射函数对花粉粒进行混沌扰动，使缺乏突变机制的花粉粒集具有较强的自适应性，有效地防止了算法后期最优解的收敛性。利用边界缓冲因子自适应缓冲跨界花粉粒，防止算法局部寻优，在处理智能物流配送中心最优选址时，算法的收敛速度和寻优精度明显提高。采用实数编码方法对算法的收敛性进行了理论分析，给出了算法的生物学模型和理论基础。实验结果表明，该方法比传统算法具有更好的性能，且优于遗传算法和粒子群算法。为智能物流配送中心选址策略提供了一种可行的解决方案。为改进和优化制造系统内部物流，提高整个智能物流系统的运行效率提供了良好的参考。©2019马里博尔大学CPE。版权所有。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Advances in Production Engineering & Management ENGINEERING, MANUFACTURINGMATERIALS SCIENC-MATERIALS SCIENCE, MULTIDISCIPLINARY

CiteScore

5.90

自引率

22.20%

发文量

期刊介绍： Advances in Production Engineering & Management (APEM journal) is an interdisciplinary international academic journal published quarterly. The main goal of the APEM journal is to present original, high quality, theoretical and application-oriented research developments in all areas of production engineering and production management to a broad audience of academics and practitioners. In order to bridge the gap between theory and practice, applications based on advanced theory and case studies are particularly welcome. For theoretical papers, their originality and research contributions are the main factors in the evaluation process. General approaches, formalisms, algorithms or techniques should be illustrated with significant applications that demonstrate their applicability to real-world problems. Please note the APEM journal is not intended especially for studying problems in the finance, economics, business, and bank sectors even though the methodology in the paper is quality/project management oriented. Therefore, the papers should include a substantial level of engineering issues in the field of manufacturing engineering.