Extraction of Product Service System Configuration Rules Based on Multi-objective DPSO Algorithm

Abstract

Abstract:

Abstract： To assist engineers to map customer requirements into technical characteristics of product service system effectively, a kind of rule extraction method combining DPSO with Pareto was proposed. The method includes establishing the model of product service system configuration rules and constructing the model of ParetoDPSO. In ParetoDPSO, continuous particle was mapped into a decimal discrete space using the frequency initialization method based on Sobol sequence and the particle discrete update method; Pareto was used to obtain the optimal set of rules by evaluating multiple target functions. By comparing with OMOPSO and DPSO, the feasibility and validity of the proposed method was verified by applying in the example of automotive product service system configuration design.

Key words: product service system, configuration rules, multiobjective optimization, Pareto, discrete particle swarm optimization (DPSO)

CLC Number:

TP 391.7

LIU Yuan1，ZHANG Zaifang1，YAO Di2，CHU Xuening3. Extraction of Product Service System Configuration Rules Based on Multi-objective DPSO Algorithm[J]. Journal of Shanghai Jiaotong University, 2015, 49(08): 1123-1130.

References

［1］张在房. 顾客需求驱动的产品服务系统方案设计技术研究［D］. 上海：上海交通大学机械与动力工程学院，2011.

［2］Shao X Y, Wang Z H, Li P G, et al. Integrating data mining and rough set for customer groupbased discovery of product configuration rules［J］. International Journal of Production Research, 2006, 44(14)：27892811.

［3］Zhang Z, Cheng H, Chu X. Aided analysis for quality function deployment with an aprioribased data mining approach［J］. International Journal of Computer Integrated Manufacturing，2010，23(7)：673686.

［4］沈瑾, 王丽亚, 隆惠君, 等. 基于神经网络规则抽取的产品服务配置规则获取［J］. 工业工程与管理， 2012，17(3)：6673.

SHEN Jin, WANG Liya, LONG Huijun, et al. Product service configuration rules acquisition based on rule extraction from neural networks［J］. Industrial Engineering and Management，2012，17(3)：6673.

［5］Chen Y S, Cheng C H, Lai C J. A hybrid procedure for extracting rules of production performance in the automobile parts industry［J］. Journal of Intelligent Manufacturing，2010，21(4)：423437.

［6］Kuo R J, Chao C M, Chiu Y T. Application of particle swarm optimization to association rule mining［J］. Applied Soft Computing，2011，11(1)：326336.

［7］GhannadRezaie M, SoltanainZadeh H, Siadat M R, et al. Medical data mining using particle swarm optimization for temporal lobe epilepsy［C］∥ IEEE Congress on Evolutionary Computation. Vancouver, BC, Canada: IEEE Press, 2006：761768.

［8］雷德明, 吴智铭. 基于粒子群优化的多目标作业车间调度［J］. 上海交通大学学报, 2007, 41(11)： 17961800.

LEI Deming, WU Zhiming. Particle swarm optimization based multiobjective job shop scheduling［J］. Journal of Shanghai Jiaotong University，2007，41(11)：17961800.

［9］Unler A, Murat A. A discrete particle swarm optimization method for feature selection in binary classification problems［J］. European Journal of Operational Research，2010，206(3)：528539.

［10］余伶俐, 蔡自兴. 改进混合离散粒子群的多种优化策略算法［J］. 中南大学学报: 自然科学版，2009，40(4)：10471053.

YU Lingli, CAI Zixing. Multiple optimization strategies for improving hybrid discrete particle swarm［J］. Journal of Central South University：Science and Technology，2009，40(4)：10471053.

［11］Beiranvand V, MobasherKashani M, Abu Bakar A. Multiobjective PSO algorithm for mining numerical association rules without a priori discretization［J］. Expert Systems with Applications， 2014， 41(9)： 42594273.

［12］任彬, 张树有, 伊国栋. 基于模糊多属性决策的复杂产品配置方法［J］. 机械工程学报, 2010,46(19)： 108116.

REN Bin, ZHANG Shuyou, YI Guodong. Configuration design of complex products based on fuzzy multiattribute decisionmaking［J］. Journal of Mechanical Engineering, 2010,46(19)：108116.

［13］Yu L, Wang L. Product portfolio identification with data mining based on multiobjective GA［J］. Journal of Intelligent Manufacturing, 2010， 21(6)： 797810.

［14］Dudas C, Ng A H C, Pehrsson L, et al. Integration of data mining and multiobjective optimisation for decision support in production systems development［J］. International Journal of Computer Integrated Manufacturing，2014，27(9)：824839.

［15］Joe S， Kuo F Y. Constructing sobol sequences with better twodimensional projections［J］. SIAM Jounal of Science Computer，2008，30(5)：26352654.

［16］DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGAII［J］. Evolutionary Computation, IEEE Transactions on, 2002，6(2)：182197.

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