数据与计算发展前沿 ›› 2022, Vol. 4 ›› Issue (2): 121-130.

doi: 10.11871/jfdc.issn.2096-742X.2022.02.011

• 技术与应用 • 上一篇    下一篇

基于海鸥优化算法的企业平衡运输问题研究

邵良杉1,2(),闻爽爽1,2,*()   

  1. 1.辽宁工程技术大学,管理科学与工程研究院,辽宁 葫芦岛 125105
    2.辽宁工程技术大学,工商管理学院,辽宁 葫芦岛 125105
  • 收稿日期:2021-06-18 出版日期:2022-04-20 发布日期:2022-04-30
  • 通讯作者: 闻爽爽
  • 作者简介:邵良杉,辽宁工程技术大学,教授,管理科学与工程学科博士生导师,辽宁省“百千万人才工程”百人层次培养人选,煤炭系统“专业技术拔尖人才”,管理科学与工程一级博士点学科带头人,辽宁工程技术大学副校长。目前主要研究方向为矿山系统工程、数据挖掘。
    本文中负责整体构思。
    SHAO Liangshan, Professor of Liaoning Technical University, doctoral supervisor of management science and engineering, training candidates at the level of 100 people for the “100 million talent projects” in Liaoning Province, “Top professional and te-chnical talents” in the coal system, first level doctoral program leader in management science and engineering, Vice president of Liaoning Technical University. At present, his main research directions are mine system engineering and data mining.
    In this paper, he is responsible for the overall idea.
    E-mail: lntushao@163.com|闻爽爽,辽宁工程技术大学,在读硕士研究生,目前主要研究方向为数据挖掘、智能优化。
    本文中负责文献调研、论文撰写和设计,修改全文。
    Wen Shuangshuang is a master’s student in Liaoning Technical University. Her research interests include data mining and intelligent optimization.
    In this paper, she is responsible for literature research, thesis design, writing and modification.
    E-mail: 18340312141@163.com
  • 基金资助:
    国家自然科学基金(71771111)

Research on Enterprise Balanced Transportation Problem Based on Seagull Optimization Algorithm

SHAO Liangshan1,2(),WEN Shuangshuang1,2,*()   

  1. 1. Institute of Management Science and Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China
    2. School of Business Administration, Liaoning Technical University, Huludao, Liaoning 125105, China
  • Received:2021-06-18 Online:2022-04-20 Published:2022-04-30
  • Contact: WEN Shuangshuang

摘要:

【目的】智能时代背景下物流需求的运输成本精准预测对于资源调度及管理起着关键作用,本研究是为了丰富当前解决运输问题的方法,简化NP-hard问题的局限性。【方法】针对企业平衡运输成本问题,归纳了当前运输问题分类,以运输总成本最小化为目标,采用了传统运输问题的平衡数学模型,并运用了国外最新智能优化算法——海鸥优化算法来求解,通过迁移、攻击寻找目标函数的最优解。【结果】仿真实验结果证明了海鸥优化算法与传统管理运筹学方法、量子粒子群算法、遗传算法的求解结果相吻合。【局限】海鸥优化算法是新兴元启发式算法,仍在不断发展演变,由于相关文献的局限性,仍有待对其进一步研究。【结论】通过本研究验证了海鸥优化算法的有效性和优越性,为企业平衡运输问题提供了新的智能优化算法解决方案。

关键词: 运输问题, 成本最小化, 海鸥优化算法, 元启发式算法, MATLAB

Abstract:

[Objective] Under the background of the intelligent era, accurate prediction of transportation cost of logistics demand plays a key role in resource scheduling and management. This paper aims to enrich the current methods to solve transportation problems and simplify the limitations of NP-hard problems. [Methods] Concerning the problem of balancing enterprise transportation costs, this paper summarizes the classification of current transportation problems. Taking the minimization of total transportation cost as the goal, this paper adopts the balanced mathematical model of traditional transportation problems and uses the latest intelligent optimization algorithm called seagull optimization algorithm to find the optimal solution through migration and attack. [Results] The simulation results show that the seagull optimization algorithm is consistent with the traditional management operations research method, quantum particle swarm optimization algorithm and genetic algorithm. [Limitations] The Seagull optimization algorithm is a new meta-heuristic algorithm which is still evolving. Due to the limitations of related literature, it still needs to be further studied. [Conclusions] This study verifies the effectiveness and superiority of the seagull optimization and provides a new intelligent optimization algorithm solution for enterprise balanced transportation problems.

Key words: transportation problem, cost minimization, seagull optimization algorithm, Meta-heuristic algorithm, MATLAB