An asymmetric multileveled symbiotic evolutionary algorithm for integrated FMS scheduling

This paper considers the integrated FMS (flexible manufacturing system) scheduling problem (IFSP) consisting of loading, routing, and sequencing subproblems that are interrelated to each other. In scheduling FMS, the decisions for the subproblems should be appropriately made to improve resource utilization. It is also important to fully exploit the potential of the inherent flexibility of FMS. In this paper, a symbiotic evolutionary algorithm, named asymmetric multileveled symbiotic evolutionary algorithm (AMSEA), is proposed to solve the IFSP. AMSEA imitates the natural process of symbiotic evolution and endosymbiotic evolution. Genetic representations and operators suitable for the subproblems are proposed. A neighborhood-based coevolutionary strategy is employed to maintain the population diversity. AMSEA has the strength to simultaneously solve subproblems for loading, routing, and sequencing and to easily handle a variety of FMS flexibilities. The extensive experiments are carried out to verify the performance of AMSEA, and the results are reported.

[1]  Jiyin Liu,et al.  The classification of FMS scheduling problems , 1996 .

[2]  Simon K.A. Robson,et al.  Book review of "The origin of sex: three billion years of genetic recombination" by Lynn Margulis and Dorion Sagan, Yale University Press, New Haven and London , 1987 .

[3]  Toni M. Somers,et al.  The measurement of manufacturing flexibility , 1992 .

[4]  Ying-Chin Ho,et al.  Solving cell formation problems in a manufacturing environment with flexible processing and routeing capabilities , 1996 .

[5]  P. Raven,et al.  ORIGIN OF EUKARYOTIC CELLS , 1971 .

[6]  Risto Miikkulainen,et al.  Forming Neural Networks Through Efficient and Adaptive Coevolution , 1997, Evolutionary Computation.

[7]  M. Selim Akturk,et al.  Integrated scheduling and tool management in flexible manufacturing systems , 2001 .

[8]  Andrew Kusiak,et al.  Application of operational research models and techniques in flexible manufacturing systems , 1986 .

[9]  G. Thompson,et al.  Algorithms for Solving Production-Scheduling Problems , 1960 .

[10]  K. Kato.  An integrated approach for loading, routeing, and scheduling in flexible manufacturing systems , 1995, Proceedings 1995 INRIA/IEEE Symposium on Emerging Technologies and Factory Automation. ETFA'95.

[11]  노환균,et al.  Due-date based loading and scheduling methods in a flexible manufacturing system with an automatic tool transporter = 공구이송이 가능한 유연제조시스템에서 납기를 고려한 부품과 공구 할당 및 일정 계획에 관한 연구 , 1996 .

[12]  Yeongho Kim,et al.  A Coevolutionary Algorithm for Balancing and Sequencing in Mixed Model Assembly Lines , 2000, Applied Intelligence.

[13]  Yeongho Kim,et al.  An Endosymbiotic Evolutionary Algorithm for Optimization , 2004, Applied Intelligence.

[14]  Christian Bierwirth,et al.  Production Scheduling and Rescheduling with Genetic Algorithms , 1999, Evolutionary Computation.

[15]  A. J. Clewett,et al.  Introduction to sequencing and scheduling , 1974 .

[16]  F. Capra.  The Web of Life , 1996 .

[17]  C. Saygin,et al.  Integrating Flexible Process Plans with Scheduling in Flexible Manufacturing Systems , 1999 .

[18]  Mary Lou Maher,et al.  Modeling design exploration as co-evolution , 1996 .

[19]  Keith Popplewell,et al.  Towards the integration of flexible manufacturing system scheduling , 1999 .

[20]  Kripa Shanker,et al.  Models and solution approaches for part movement minimization and load balancing in FMS with machine, tool and process plan flexibilities , 1995 .

[21]  Jesuk Ko,et al.  A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling , 2003, Comput. Oper. Res..

[22]  Kripa Shanker,et al.  A genetic algorithm for FMS part type selection and machine loading , 2000 .

[23]  Kathryn E. Stecke,et al.  Design, planning, scheduling, and control problems of flexible manufacturing systems , 1985 .

[24]  Hing Kai Chan,et al.  The State of the Art in Simulation Study on FMS Scheduling: A Comprehensive Survey , 2002 .

[25]  N. Raman,et al.  FMS planning decisions, operating flexibilities, and system performance , 1995 .

[26]  Mitchell A. Potter,et al.  The design and analysis of a computational model of cooperative coevolution , 1997 .

[27]  김재윤,et al.  공생진화 알고리듬에서의 공생파트너 선택전략 분석 ( Analysis of Partnering Strategies in Symbiotic Evolutionary Algorithms ) , 2000 .

[28]  Yeo Keun Kim,et al.  Multileveled Symbiotic Evolutionary Algorithm: Application to FMS Loading Problems , 2005, Applied Intelligence.

[29]  Gilbert Syswerda,et al.  A Study of Reproduction in Generational and Steady State Genetic Algorithms , 1990, FOGA.

[30]  Mansour E. Abou Gamila,et al.  A modeling technique for loading and scheduling problems in FMS , 2003 .

[31]  Fernando Guerrero,et al.  MACHINE LOADING AND PART TYPE SELECTION IN FLEXIBLE MANUFACTURING SYSTEMS , 1999 .