Filtered-beam-search-based algorithm for dynamic rescheduling in FMS

In the practical production process of a flexible manufacturing system (FMS), unexpected disturbances such as rush orders arrival and machine breakdown may inevitably render the existing schedule infeasible. This makes dynamic rescheduling necessary to respond to the disturbances and to improve the efficiency of the disturbed FMS. Compared with the static scheduling, the dynamic rescheduling relies on more effective and robust search approaches for its critical requirement of real-time optimal response. In this paper, a filtered-beam-search (FBS) -based heuristic algorithm is proposed to solve the dynamic rescheduling problem in a large and complicated job shop FMS environment with realistic disturbances. To enhance its performance, the proposed algorithm makes improvement in the local/global evaluation functions and the generation procedure of branches. With respect to a due date-based objective (weighted quadratic tardiness), computational experiments are studied to evaluate the performance of the proposed algorithm in comparison with those of other popular methods. The results show that the proposed FBS-based algorithm performs very well for dynamic rescheduling in terms of computational efficiency and solution quality.

[1]  Lifeng Xi,et al.  A beam-search-based algorithm for the tool switching problem on a flexible machine , 2005 .

[2]  Yuehwern Yih,et al.  A competitive neural network approach to multi-objective FMS scheduling , 1998 .

[3]  Joseph J. Talavage,et al.  A transient-based real-time scheduling algorithm in FMS , 1991 .

[4]  Yeong-Dae Kim,et al.  A real-time scheduling mechanism for a flexible manufacturing system: Using simulation and dispatching rules , 1998 .

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

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

[7]  Krishna R. Pattipati,et al.  A practical approach to job-shop scheduling problems , 1993, IEEE Trans. Robotics Autom..

[8]  Hing Kai Chan,et al.  Dynamic Scheduling for a Flexible Manufacturing System - The Pre-emptive Approach , 2001 .

[9]  I. Sabuncuoglu,et al.  A beam search-based algorithm and evaluation of scheduling approaches for ̄ exible manufacturing systems , 2022 .

[10]  Kathryn E. Stecke,et al.  Loading and control policies for a flexible manufacturing system , 1981 .

[11]  Ihsan Sabuncuoglu,et al.  Rescheduling frequency in an FMS with uncertain processing times and unreliable machines , 1999 .

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

[13]  W. Tsai,et al.  Time complexity of a path formulated optimal routing algorithm (second printing) , 1994, IEEE Trans. Autom. Control..

[14]  Wu Zhiming,et al.  The application of Adaptive Genetic Algorithms in FMS dynamic rescheduling , 2003, Int. J. Comput. Integr. Manuf..

[15]  Ihsan Sabuncuoglu,et al.  Job shop scheduling with beam search , 1999, Eur. J. Oper. Res..

[16]  Zoe Doulgeri,et al.  A hierarchical knowledge-based scheduling and control for FMSs , 1993 .

[17]  Yeong-Dae Kim,et al.  Simulation-based real-time scheduling in a flexible manufacturing system , 1993 .

[18]  Chinyao Low,et al.  Modelling and heuristics of FMS scheduling with multiple objectives , 2006, Comput. Oper. Res..

[19]  Takashi Sekiguchi,et al.  A timed Petri net and beam search based online FMS scheduling system with routing flexibility , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[20]  P. Ow,et al.  Filtered beam search in scheduling , 1988 .

[21]  Shoichi Noguchi,et al.  A Real-Time Scheduler Using Neural Networks for Scheduling Independent and Nonpreemptable Tasks with Deadlines and Resource Requirements , 1993 .

[22]  Frank DiCesare,et al.  FMS scheduling using Petri nets and heuristic search , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[23]  Garng M. Huang,et al.  Time complexity of a path formulated optimal routing algorithm , 1994, IEEE Trans. Autom. Control..

[24]  H. M. Shih.  Fuzzy inference and beam search based scheduling , 1994, Proceedings of 1994 IEEE International Conference on Industrial Technology - ICIT '94.

[25]  Mark A. Coffin,et al.  R&D project selection and scheduling with a filtered beam search approach , 1996 .

[26]  Anita Lee,et al.  Flexible manufacturing system (FMS) scheduling using filtered beam search , 1990, J. Intell. Manuf..

[27]  Min-Hong Han,et al.  Real-time tool control and job dispatching in flexible manufacturing systems , 1989 .

[28]  Hirofumi Matsuo,et al.  A bottleneck-based beam search for job scheduling in a flexible manufacturing system , 1989 .

[29]  Ihsan Sabuncuoglu,et al.  Reactive scheduling in a dynamic and stochastic FMS environment , 2003 .

[30]  Hing Kai Chan,et al.  Analysis of dynamic dispatching rules for a flexible manufacturing system , 2003 .

[31]  Ihsan Sabuncuoglu,et al.  Analysis of reactive scheduling problems in a job shop environment , 2000, Eur. J. Oper. Res..

[32]  Jiyin Liu,et al.  General heuristic procedures and solution strategies for FMS scheduling , 1999 .

[33]  Semra Tunali.  Evaluation of alternate routing policies in scheduling a job-shop type FMS , 1997 .