系统仿真学报 ›› 2019, Vol. 31 ›› Issue (5): 901-908.doi: 10.16182/j.issn1004731x.joss.17-0160

• 仿真系统与技术 • 上一篇    下一篇

基于遗传算法的舰载装备多目标作业调度优化研究

鲍劲松, 李志强, 周亚勤   

  1. 东华大学,上海 201600
  • 收稿日期:2017-04-19 修回日期:2017-07-07 出版日期:2019-05-08 发布日期:2019-11-20
  • 通讯作者: 周亚勤(1978-), 女, 江苏, 博士, 副教授, 硕导, 研究方向为智能生产调度与控制等。
  • 作者简介:鲍劲松(1972-), 男, 安徽, 博士, 副教授, 博导, 研究方向为智能制造、复杂系统建模与仿真等; 李志强(1996-), 男, 安徽, 硕士生, 研究方向为智能调度等;
  • 基金资助:
    国家自然科学基金(51475301)

Multi-Objective Operation Scheduling Optimization of Shipborne-equipment Based on Genetic Algorithm

Bao Jinsong, Li Zhiqiang, Zhou Yaqin   

  1. Donghua University, Shanghai 201600, China
  • Received:2017-04-19 Revised:2017-07-07 Online:2019-05-08 Published:2019-11-20

摘要: 舰载装备的作业调度是多任务模式下的复杂组合优化问题。已有研究主要针对单一目标优化,而实际往往需同时优化路径、时长、资源等多个目标。以两栖登陆舰舰载装备出库前的作业调度为研究对象,在考虑先序约束的基础上,对作业时长及资源用量同时进行优化。分析建立了该作业调度的多目标优化模型,利用遗传算法求解;针对两目标设计了可自适应调整的适应度函数,并对编码方式及遗传算子进行设计;实例仿真,验证算法可以高效地同时优化调度作业时长和资源用量。

关键词: 舰载装备, 作业调度, 先序约束, 多目标优化, 遗传算法

Abstract: Multi-objective operation scheduling of shipborne equipment is a complex combinational optimization problem under multi-task system. Existing research focuses mainly on single-objective optimization while several other objectives need to be considered during real operation such as path, duration, resource, etc. Considering the operation scheduling before exporting of an amphibious landing ship as the research object, both scheduling duration and resource requirement under the precedence constraint are optimized. The mathematical model of this multi-objective operation scheduling is established and solved using genetic algorithm. A fitness function which can be self-adaptively adjusted is designed; an adapting encoding strategy, a crossover operator, and a mutation operator are also designed during the solution. The result of the instance simulation indicates that the algorithm is effective and reliable to optimize duration and resource requirements during the operation scheduling.

Key words: shipborne-equipment, operation scheduling, precedence constraint, multi-objective optimization, genetic algorithm

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