求解多目标柔性作业车间调度问题的两阶段混合Pareto蚁群算法

赵博选; 高建民; 陈琨

doi:10.7652/xjtuxb201607022

您当前的位置：

首页 >

文章列表页 >

求解多目标柔性作业车间调度问题的两阶段混合Pareto蚁群算法

更新时间：2025-07-09

- 求解多目标柔性作业车间调度问题的两阶段混合Pareto蚁群算法
- Two-Stage Hybrid Pareto Ant Colony Algorithm for Multi-Objective Flexible Job Shop Scheduling
- 西安交通大学学报 2016年50卷第7期页码：145-151
- 作者机构：
  
  西安交通大学机械工程学院,西安,710049
- 作者简介：
- 基金信息：
  
  : 2015-11-23。作者简介: 赵博选(1986—),男,博士生;高建民(通信作者),男,教授,博士生导师。基金项目: 国家科技重大专项资助项目(2012ZX04010-071)
- DOI：10.7652/xjtuxb201607022
  中图分类号： F406.2
- 网络首发：2016-07-10，
  
  纸质出版：2016
- 稿件说明：
移动端阅览
赵博选, 高建民, 陈琨. 求解多目标柔性作业车间调度问题的两阶段混合Pareto蚁群算法[J]. 西安交通大学学报, 2016,50(7):145-151.

Two-Stage Hybrid Pareto Ant Colony Algorithm for Multi-Objective Flexible Job Shop Scheduling[J]. 2016, 50(7): 145-151.
赵博选, 高建民, 陈琨. 求解多目标柔性作业车间调度问题的两阶段混合Pareto蚁群算法[J]. 西安交通大学学报, 2016,50(7):145-151. DOI： 10.7652/xjtuxb201607022.

Two-Stage Hybrid Pareto Ant Colony Algorithm for Multi-Objective Flexible Job Shop Scheduling[J]. 2016, 50(7): 145-151. DOI： 10.7652/xjtuxb201607022.

摘要

针对多目标柔性作业车间调度问题(FJSP)分解得到的作业分派、排序子问题仍是多目标优化问题的情况

提出了一种求解该问题的分层Pareto优化框架

并采用该框架构建了两阶段混合Pareto蚁群算法的求解算法

其中两个Pareto蚁群系统分别求解多目标作业分派、排序问题。结合GT算法、排产规则评估和过滤第一阶段的分派方案

将具有较好评估全局解的分派方案作为分派阶段的精英档案

并输入给排序蚁群系统获取其非支配调度解

进而获取问题全局非支配解。子问题算法混合了各目标相关的邻域搜索策略

与Pareto蚁群算法结合

以期提高解的质量。通过求解带有平均工件加权延迟时间指标的多个FJSP基准算例

验证了算法的有效性。计算结果表明

该分层Pareto优化框架对原问题进行分层分解

有利于降低原问题的复杂性

相比多数文献

算法能够获得各基准算例Pareto非支配解

从而为分解求解复杂多目标调度优化问题提供了一种途径。

Abstract

Multi-objective flexible job shop scheduling can be divided into two sub-problems

namely job assignment and sorting

which are often multi-objective optimization problems. Aiming at this situation

this paper presents a layered Pareto optimization frame for multi-objective flexible job shop problem and proposes a two-stage hybrid Pareto ant colony algorithm for multi-objective operation assignment(OA)and operation sequencing(OS)sub-problems. Embedding multiple scheduling rules in GT algorithm is used to evaluate and filter the assignment solutions. The global optimal non-dominated front of the original problem is obtained by scheduling optimization as the elite archive of assignments. Each Pareto ant colony algorithm is combined with the neighborhood search strategies related to different objectives. The co-evolutionary can obtain high-quality solutions to multi-objective FJSP. Finally

by solving four benchmark instances considering minimizing the mean weighted tardiness time

the effectiveness of the method is testified. The simulation results show that the layered Pareto optimization frame helps to reduce complexity of the problem

and compared with other literatures

the proposed algorithm can obtain the Pareto non-dominant solutions of each instance

providing a new way for solving complex multi-objective scheduling problems.

关键词

Keywords

references

莫建麟, 吴喆. 基于混合遗传禁忌的多目标柔性作业车间调度 [J]. 重庆师范大学学报(自然科学版), 2013, 30(2): 87-91.

MO Jianlin, WU Zhe. Multi-objective flexible job shop scheduling based on hybrid genetic & tabu algorithm [J]. Journal of Chongqing Normal University(Natural Science), 2013, 30(2): 87-91.

张超勇, 董星, 王晓娟, 等. 基于改进非支配排序遗传算法的多目标柔性作业车间调度 [J]. 机械工程学报, 2010, 46(11): 156-164.

ZHANG Chaoyong, DONG Xing, WANG Xiaojuan, et al. Improved NSGA-II for the multi-objective flexible job-shop scheduling problem [J]. Journal of Mechanical Engineering, 2010, 46(11): 156-164.

MOSLEHI G, MAHNAM M. A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search [J]. International Journal of Production Economics, 2011, 129(1): 14-22.

GAO K Z, SUGANTHAN P N, PAN Q K. Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling [J]. Information Sciences, 2014, 289(1): 76-79.

张洁, 张朋, 刘国宝. 基于两阶段蚁群算法的带非等效并行机的作业车间调度 [J]. 机械工程学报, 2013, 49(6): 136-144.

ZHANG Jie, ZHANG Peng, LIU Guobao. Two-stage ant colony algorithm based job shop scheduling with unrelated parallel machines [J]. Journal of Mechanical Engineering, 2013, 49(6): 136-144.

XING Lining, CHEN Yingwu. An efficient search method for multi-objective flexible job shop scheduling problems [J]. Journal of Intelligent Manufacturing, 2009, 20(3): 283-293.

XING Lining, CHEN Yingwu. Multi-objective flexible job shop schedule: design and evaluation by simulation modeling [J]. Applied Soft Computing, 2009, 9(1): 362-376.

XIA Weijun, WU Zhiming. An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems [J]. Computers Industrial Engineering, 2005, 48(2): 409-425.

LI Junqing, PAN Q, LIANG Y C. An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems [J]. Computers Industrial Engineering, 2010, 59(4): 647-662.

CHIANG T C, LIN H J. A simple and effective evolutionary algorithm for multi-objective flexible job shop scheduling [J]. International Journal of Production Economics, 2013, 141(1): 87-98.

GARCIA-MARTINEZ C, CORDON O, HERRERA F. A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP [J]. European Journal of Operational Research, 2007, 180(1): 116-148.

DOERNER K, GUTJAHR W J. Pareto ant colony optimization: a meta-heuristic approach to multi-objective portfolio selection [J]. Annals of Operations Research, 2004, 131(1): 79-99.

刘岳镭,冯祖仁,任晓栋.具有恶化效应的双代理单机最优调度算法.2016,50(6):9-14.[doi:10.7652/xjtuxb201606002]

陈鹏飞,李昕怡,齐勇,等.单步启发式策略的备份虚拟机复用策略.2016,50(1):100-107.[doi:10.7652/xjtuxb201601 016]

杨鹏飞,王泉.片上网络异构多核系统任务调度与映射.2015,49(6):72-76.[doi:10.7652/xjtuxb201506012]

王丽霞,曲桦,赵季红,等.软件定义网络中应用二值粒子群优化的控制器部署策略.2015,49(6):67-71.[doi:10.7652/xjtuxb201506011]

周光辉,苗发祥,李彦广.数控加工中心任务与刀具集成调度模型及改进自适应遗传算法.2014,48(12):1-7.[doi:10.7652/xjtuxb201412001]

邵成成,王锡凡,王秀丽,等.主动配电系统与主网的有功协调.2014,48(11):58-63.[doi:10.7652/xjtuxb201411010]

李彬,宋立明,李军,等.长叶片透平级多学科多目标优化设计.2014,48(1):1-6.[doi:10.7652/xjtuxb201401001]

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

EBSILON软件在热电联产系统优化中的应用综述

融合物理信息与深度算子网络的变压器绕组热-流场快速计算方法

隧道内燃料电池汽车氢气泄漏扩散特性及影响因素

超临界二氧化碳向心透平轮背间隙内风阻损失及流动特性研究

多工况下离心压气机叶轮-机匣一体联合设计优化