摘要
针对加工资源和运输资源集成下绿色作业车间调度问题,通过研究生产车间综合能耗模型,建立了机器和自动导引小车(Automated guided vehicle,AGV)集成调度下多目标优化模型。提出一种改进分布估计算法(Improved estimation of distribution algorithm,IEDA)对模型进行求解。首先,采用优良种群作为样本学习来构建概率分布模型以提高IEDA的全局搜索能力;然后基于一种类似激素调控机制的速度冷却控制方法设计出新的模拟退火函数,并将其融入到分布估计算法中以提高IEDA的局部搜索能力。最后通过数值实验来验证所提模型和算法的可行性和有效性。
Aiming at the green job shop scheduling problem under the integration of processing resources and transportation resources,a multi-objective optimization model based on the integrated scheduling of machines and automated guided vehicle(AGV)is established by studying the comprehensive energy consumption in production workshop.An improved estimation of distribution algorithm(IEDA)is proposed to solve the problem.First,excellent individuals are generated as sample learning to construct the probability distribution model for improving the global search ability of IEDA.Then,inspired by the hormone regulation mechanism,a new speed cooling control method is designed in simulated annealing algorithm to improve the local search ability of IEDA.Finally,numerical experiments are conducted and the results show the feasibility and effectiveness of the proposed model and algorithm.
作者
戴敏
张玉伟
曾励
DAI Min;ZHANG Yuwei;ZENG Li(College of Mechanical Engineering,Yangzhou University,Yangzhou,225127,China)
出处
《南京航空航天大学学报》
EI
CAS
CSCD
北大核心
2020年第3期468-477,共10页
Journal of Nanjing University of Aeronautics & Astronautics
基金
国家科技部重点研发(2016YFD0700903)资助项目
江苏省高等学校自然科学研究面上(17KJB460018)资助项目
扬州市创新能力计划项目-高等院校合作专项(YZ2017278)资助项目
扬州大学教学改革研究课题(YZUJX2018-28B)资助项目。
关键词
绿色作业车间
集成调度
综合能耗
分布估计算法
green job shop
integrated scheduling
comprehensive energy consumption
estimation of distribution algorithm
