计算机科学 ›› 2017, Vol. 44 ›› Issue (4): 246-251.doi: 10.11896/j.issn.1002-137X.2017.04.052

• 人工智能 • 上一篇    下一篇

基于果蝇优化算法的多工位装配序列规划

袁文兵,常亮,徐周波,古天龙   

  1. 桂林电子科技大学广西可信软件重点实验室 桂林541004,桂林电子科技大学广西可信软件重点实验室 桂林541004,桂林电子科技大学广西可信软件重点实验室 桂林541004,桂林电子科技大学广西可信软件重点实验室 桂林541004
  • 出版日期:2018-11-13 发布日期:2018-11-13
  • 基金资助:
    本文受国家自然科学基金(61572146,0,U1501252),广西自然科学基金(2015GXNSFAA139285,2014GXNSFAA118354),广西可信软件重点实验室,广西高等学校高水平创新团队及卓越学者计划,桂林电子科技大学研究生教育创新计划(YJCXS201509)资助

Multi-plant Assembly Sequence Planning Based on Fruit Fly Optimization Algorithm

YUAN Wen-bing, CHANG Liang, XU Zhou-bo and GU Tian-long   

  • Online:2018-11-13 Published:2018-11-13

摘要: 为同时解决产品装配序列规划和多工位分配问题,提出一种面向复杂产品的基于果蝇优化算法的多工位装配序列规划方法。首先,基于果蝇优化算法设计了针对求解序列的编码体系;其次,采用多子种群并行搜索模式,重新设计了果蝇优化算法的搜索过程;然后,为了综合考虑多工位上相关装配操作成本的影响,提出了新的适应度函数表达式,并将适应度函数与优先序列矩阵结合起来对进化过程进行引导,实现了对产品装配序列和工位分配顺序的优化;最后,以飞机起落架为例,验证了所提方法在解决多目标优化问题方面的有效性。

关键词: 果蝇优化算法,多工位,装配序列规划,多目标优化

Abstract: An improved fruit fly optimization algorithm(FOA) was proposed to solve the distribution problem of assembly sequence planning and plant assignment.Firstly,in the multi-plant assembly sequence planning model,the coding system of FOA is given.Secondly,it uses multiple fruit fly groups to enhance the parallel search ability of the FOA.According to the characteristics of the improved FOA,a smell-based search and a vision-based search are well designed for the groups to stress its exploitation.And a cooperative search process is developed to stress its exploration.Thirdly,the fitness function is proposed with comprehensive consideration of assembly operation cost,assembly tool change cost,the clamping change cost and general transportation cost.Moreover,the feasible assembly sequences and station allocation are guided by assembly precedence matrix (APM) and fitness function.At same time,they are optimized based on the improved FOA.Finally,an example of the product is tested and illustrated.The test results show that the presented method is feasible and efficient for solving the multi-plant assembly sequence planning problem.

Key words: Fruit fly optimization algorithm,Multi-plant optimization,Assembly sequence planning,Multi-objective optimization

[1] WANG J F,LI S Q,LIU J H,et al.Computer aided assembly planning a survey[J].Journal of Engineering Graphics,2005,26(2):1-6.(in Chinese) 王俊峰,李世其,刘继红,等.计算机辅助装配规划研究综述[J].工程图学学报,2005,6(2):1-6.
[2] DE MELLO H.A Correct and Complete Algorithm for the Ge-neration of Mechanical Assembly Sequences[J].IEEE Transaction Robotics and Automation,1991,2(7):228-240.
[3] GOTTIPOL U R B,GHOSH K.A simplified and efficient representation for evaluation and selection of assembly sequences[J].Computers in Industry,2003,50(3):251-264.
[4] LI R,FU Y L,FENG H B.Assembly sequence planning based on connecter-structure knowledge[J].Computer Integrated Manufacturing Systems,2008,14(6):1130-1135.(in Chinese) 李荣,付宜利,封海波.基于连接结构知识的装配序列规划[J].计算机集成制造系统,2008,4(6):1130-1135.
[5] WANG Y,LIU J H,LI L S.Assembly sequence merging based on assembly unit partitioning [J].International Journal of Advanced Manufacturing Technology,2009,45(7):808-820.
[6] SMITH G C,SMITH S.An enhanced genetic algorithm for automated assembly planning[J].Robotics and Computer Integra-ted Manufacturing,2000,18(5):355-364.
[7] ZENG B,LI M F,ZHANG Y.Assembly sequence planningbased on improved firelyalgorithm[J].Computer Integrated Manufacturing Systems,2014,20(4):799-806.(in Chinese) 曾冰,李明富,张翼.基于改进萤火虫算法的装配序列规划方法[J].计算机集成制造系统,2014,0(4):799-806.
[8] NING L H,GU T L.Immune algorithm for assembly sequence planning problem[J].Computer Integrated Manufacturing Systems,2007,3(4):762-769.(in Chinese) 宁黎华,古天龙.基于免疫算法的装配序列规划问题求解[J].计算机集成制造,2007,3(4):762-769.
[9] SHI S C,LI R,FU Y L,et al.Assembly sequence planning based on improved ant colony algorithm[J].Machinery Design & Manufacture,2010,6(6):1189-1194.(in Chinese) 史士财,李荣,付宜利,等.基于改进蚁群算法的装配序列规划[J].计算机集成制造系统,2010,6(6):1189-1194.
[10] WANG F C,SUN Y C,LI N.Multi Station Assembly Sequence Planning Based on Particle Swarm Optimization Algorithm[J].Journal of Mechanical Engineering,2012,8(9):1-8.(in Chinese) 王丰产,孙有朝,李娜.多工位装配序列粒子群优化算法[J].机械工程学报,2012,8(9):1-8.
[11] PAN W T.A new fruit fly optimisation algorithm:taking the financial distress model as an example[J].Knowledge-Based Systems,2012(2):69-74.
[12] HAN J,WANG P,YANG X.Tuning of PID controller based on fruit fly optimisation algorithm[C]∥International Conference on Mechatronics & Automation.2012:409-413.
[13] WANG L,ZHENG X L,WANG S Y.A novel binary fruit fly optimisation algorithm for solving the multidimensional knapsack problem[J].Knowledge-Based Systems,2013,48(2):217-23.
[14] LIN S M.Analysis of service satisfaction in web auction logistics service using a combination of Fruit fly optimisation algorithm and general regression neural network[J].Neural Computing and Applications,2013,22(3):783-791.
[15] SHENG W,BAO Y.Fruit fly optimisation algorithm based fractional order fuzzyPID controller for electronic throttle[J].Nonlinear Dynamics,2013,73(1/2):611-619.
[16] LI J Q,PAN Q K,KUN M,et al.Solving the steelmaking cas-ting problem using an effective fruit fly optimization algorithm[J].Knowledge-Based Systems,2014,72(5):28-36.
[17] MOUSAVI S M,ALIKAR N,NIAKI S T A.Optimization a location allocation-inventory problem in a two-echelon supply chain network:A modified fruit fly optimization algorithm[J].Computer & Industrial Engineering,2015,87(c):543-560.
[18] NIU J W,ZHONG W M,LIANG Y.Fruit fly optimization algorithm based on differential evolution and its application on gasification process operation optimization[J].Knowledge-Based Systems,2015,88(c):253-263.
[19] WANG L,LIU R,LIU S.An effective and efficient fruit fly optimization algorithm with levelprobability policy and itsapplications[J].Knowledge-Based Systems,2016,97(c):158-174.
[20] LEI X,DING Y,FUJITA H.Identification of dynamic protein complexes based on fruit fly optimization algorithm[J].Know-ledge-Based Systems,2016,105(c):270-277.
[21] WANG X J,GAO L,ZHANG C Y, et al.Amulti-objective genetical Gorithm based on immune and entropy principle for flexi-ble job-shop scheduling problem[J].The International Journal of Advanced Manufacturing Technology,2010,51(5):757-767.
[22] MONTGOMERY D C.Design and Analysis of Experiments[J].Journal of the American Statistical Association,2005,81(16):308.

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