系统仿真学报 ›› 2018, Vol. 30 ›› Issue (11): 4403-4412.doi: 10.16182/j.issn1004731x.joss.201811042

• 仿真应用工程 • 上一篇    下一篇

花授粉算法求解多目标模糊柔性作业车间调度

徐文豪, 王艳, 严大虎, 纪志成   

  1. 江南大学 物联网技术应用教育部工程研究中心,无锡 214122
  • 收稿日期:2018-05-12 修回日期:2018-06-02 发布日期:2019-01-04
  • 作者简介:徐文豪(1993-),男,江苏太仓,硕士生,研究方向为智能调度与群体智能算法;王艳(1978-),女,江苏盐城,教授,研究方向为制造系统能效优化。
  • 基金资助:
    国家自然科学基金(61572238),江苏省杰出青年基金(BK20160001)

Flower Pollination Algorithm for Multi-Objective Fuzzy Flexible Job Shop Scheduling

Xu Wenhao, Wang Yan, Yan Dahu, Ji Zhicheng   

  1. Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China
  • Received:2018-05-12 Revised:2018-06-02 Published:2019-01-04

摘要: 针对实际工厂柔性生产过程中存在的参数不确定性问题,建立了一种多目标模糊柔性作业车间调度数学模型。为求解所建模型,将加工时间、加工成本、原材料成本用三角模糊数表示,以最小化最大完工时间和生产成本为优化目标。提出一种改进的自适应离散花授粉算法(ADMOFPA),并在初始化阶段运用离散算子将解进行离散化处理。为增强算法全局搜索和局部开发的能力,在迭代过程中引入自适应变异算子。将所提算法运用于某柔性生产车间实例进行仿真测试,并与基本花授粉算法和粒子群算法作对比,证明了所提方法的有效性。

关键词: 多目标调度, 模糊柔性作业车间, 生产成本, 三角模糊数, 花授粉算法, 自适应算子

Abstract: For the uncertainty of parameters during flexible industrial process in the manufacturing workshops, a model of multi-objective fuzzy flexible job shop scheduling is established. To solve this model, the processing time, processing cost and material cost are described by triangular fuzzy numbers to minimize the makespan and production cost. An adaptive discrete flower pollination algorithm (ADMOFPA) is proposed. A discrete operator is utilized in the algorithm to discretize the solutions at the initialization period. To enhance the global exploration and local exploitation ability of ADMOFPA, an adaptive mutation operator is adopted. By simulating the instance of one flexible production workshop using the proposed algorithm, the results validate the effectiveness of the proposed algorithm compared with the basic FPA and particle swarm optimization.

Key words: multi-objective scheduling, fuzzy flexible job shop, triangular fuzzy numbers, flower pollination algorithm, production cost, discrete operator

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