计算机技术与发展
計算機技術與髮展
계산궤기술여발전
COMPUTER TECHNOLOGY AND DEVELOPMENT
2015年
5期
68-73
,共6页
机器人单元调度%柔性%Job Shop%量子粒子群优化%混沌
機器人單元調度%柔性%Job Shop%量子粒子群優化%混沌
궤기인단원조도%유성%Job Shop%양자입자군우화%혼돈
scheduling of robotic manufacturing cell%flexible%Job Shop%quantum-behaved particle swarm optimization%chaotic
柔性Job Shop类型机器人制造单元调度问题是一类新的具有广泛工程应用背景而又极富挑战的调度问题,引起了学术界和工业界的极大关注。文中分析了柔性Job Shop类型机器人单元调度问题的内容与特点,并以模具生产为背景,构建了一种以工件组最大完工时间最小为目标的Job Shop类型机器人单元调度模型,进而提出了一种混沌量子粒子群算法( CQPSO)用于模型求解。该算法在量子粒子群算法( QPSO)基础上,引入改进的Tent混沌映射机制,在保持QPSO算法收敛速度快的同时,克服了其易陷入局部极小值的缺点,提高了算法求解效率。仿真实验结果表明,CQPSO算法在求解柔性Job Shop类型机器人调度问题方面具有较大的应用优势。
柔性Job Shop類型機器人製造單元調度問題是一類新的具有廣汎工程應用揹景而又極富挑戰的調度問題,引起瞭學術界和工業界的極大關註。文中分析瞭柔性Job Shop類型機器人單元調度問題的內容與特點,併以模具生產為揹景,構建瞭一種以工件組最大完工時間最小為目標的Job Shop類型機器人單元調度模型,進而提齣瞭一種混沌量子粒子群算法( CQPSO)用于模型求解。該算法在量子粒子群算法( QPSO)基礎上,引入改進的Tent混沌映射機製,在保持QPSO算法收斂速度快的同時,剋服瞭其易陷入跼部極小值的缺點,提高瞭算法求解效率。倣真實驗結果錶明,CQPSO算法在求解柔性Job Shop類型機器人調度問題方麵具有較大的應用優勢。
유성Job Shop류형궤기인제조단원조도문제시일류신적구유엄범공정응용배경이우겁부도전적조도문제,인기료학술계화공업계적겁대관주。문중분석료유성Job Shop류형궤기인단원조도문제적내용여특점,병이모구생산위배경,구건료일충이공건조최대완공시간최소위목표적Job Shop류형궤기인단원조도모형,진이제출료일충혼돈양자입자군산법( CQPSO)용우모형구해。해산법재양자입자군산법( QPSO)기출상,인입개진적Tent혼돈영사궤제,재보지QPSO산법수렴속도쾌적동시,극복료기역함입국부겁소치적결점,제고료산법구해효솔。방진실험결과표명,CQPSO산법재구해유성Job Shop류형궤기인조도문제방면구유교대적응용우세。
Flexible Job Shop scheduling problem of robotic manufacturing cell is a new kind of scheduling problem with wide engineering application background and tough challenges,which attracts much attention of academia and industry. The content and features of flexible Job Shop scheduling problem of robotic manufacturing cell were analyzed,a scheduling model based on molds manufacturing with the op-timizing targets to minimal makespan was proposed in this paper. A Chaotic Quantum-behaved Particle Swarm Optimization algorithm (CQPSO) was put forward to solve the model. Based on the Quantum-behaved Particle Swarm Optimization (QPSO),the improved Tend chaotic mapping mechanism was introduced. The shortcoming of easily falling into local minimum for QPSO could be avoided, meanwhile,the fast convergence speed of QPSO could be kept in this algorithm. So the effectiveness of algorithm was improved. The sim-ulation results show that CQPSO could effectively solved the flexible Job Shop scheduling problem of robotic manufacturing cell.