The Integration of FMS Process Planning and Scheduling Using an Asymmetric Multileveled Symbiotic Evolutionary Algorithm

This paper addresses the integrated problem of process planning and scheduling in FMS (Flexible Manufacturing System). The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called asymmetric multileveled symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. Efficient genetic representations and operator schemes are considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and existing evolutionary algorithms. The experimental results show that the proposed algorithm outperforms the compared algorithms.

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

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

[3]  Ram Rachamadugu,et al.  Classification and review of FMS scheduling procedures , 1994 .

[4]  Neil A. Campbell,et al.  Biology: Concepts & Connections , 1987 .

[5]  Jan Paulli,et al.  A hierarchical approach for the FMS scheduling problem , 1995 .

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

[7]  Thom Hodgson,et al.  Scheduling with alternatives: a link between process planning and scheduling , 1999 .

[8]  Yeo Keun Kim,et al.  A Multi-level Symbiotic Evolutionary Algorithm for FMS Loading Problems with Various Flexibilities , 2003 .

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

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

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

[12]  Ihsan Sabuncuoglu,et al.  A STUDY OF SCHEDULING RULES OF FLEXIBLE MANUFACTURING SYSTEMS : A SIMULATION APPROACH , 1998 .

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

[14]  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 .

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

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

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

[18]  Jiyin Liu,et al.  A global MILP model for FMS scheduling , 1997, Eur. J. Oper. Res..

[19]  Norhashimah Morad,et al.  Genetic algorithms in integrated process planning and scheduling , 1999, J. Intell. Manuf..

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

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