An artificial immune system for solving production scheduling problems: a review

This article reviews the production scheduling problems focusing on those related to flexible job-shop scheduling. Job-shop and flexible job-shop scheduling problems are one of the most frequently encountered and hardest to optimize. This article begins with a review of the job-shop and flexible job-shop scheduling problem, and follow by the literature on artificial immune systems (AIS) and suggests ways them in solving job-shop and flexible job-shop scheduling problems. For the purposes of this study, AIS is defined as a computational system based on metaphors borrowed from the biological immune system. This article also, summarizes the direction of current research and suggests areas that might most profitably be given further scholarly attention.

[1]  Fariborz Jolai,et al.  A variable neighborhood search for job shop scheduling with set-up times to minimize makespan , 2009, Future Gener. Comput. Syst..

[2]  C. Janeway,et al.  The immune system evolved to discriminate infectious nonself from noninfectious self. , 1992, Immunology today.

[3]  Egon Balas,et al.  The Shifting Bottleneck Procedure for Job Shop Scheduling , 1988 .

[4]  M. Eaman.  Immune system. , 2000, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[5]  I L Weissman,et al.  How the immune system develops. , 1993, Scientific American.

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

[7]  G W Hoffmann,et al.  A neural network model based on the analogy with the immune system. , 1986, Journal of theoretical biology.

[8]  Nhu Binh Ho,et al.  GENACE: an efficient cultural algorithm for solving the flexible job-shop problem , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[9]  Yoshiteru Ishida.  Fully distributed diagnosis by PDP learning algorithm: towards immune network PDP model , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[10]  Mitsuo Gen,et al.  Solving job-shop scheduling problems by genetic algorithm , 1994, Proceedings of IEEE International Conference on Systems, Man and Cybernetics.

[11]  A. Land,et al.  An Automatic Method for Solving Discrete Programming Problems , 1960, 50 Years of Integer Programming.

[12]  Pierre Borne,et al.  Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems , 2002, IEEE Trans. Syst. Man Cybern. Part C.

[13]  Fabio Freschi,et al.  Comparison of artificial immune systems and genetic algorithms in electrical engineering optimization , 2006 .

[14]  Jeffrey W. Herrmann,et al.  Improving Production Scheduling : Integrating Organizational , Decision-Making , and Problem-Solving Perspectives , 2006 .

[15]  F. Pezzella,et al.  A genetic algorithm for the Flexible Job-shop Scheduling Problem , 2008, Comput. Oper. Res..

[16]  Alan S. Perelson,et al.  The immune system, adaptation, and machine learning , 1986 .

[17]  Peter Ross,et al.  Producing robust schedules via an artificial immune system , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[18]  Marco Dorigo,et al.  New Ideas in Optimisation , 1999 .

[19]  J. C. Tay,et al.  Applying the Clonal Selection Principle to Find Flexible Job-Shop Schedules , 2005, ICARIS.

[20]  Ailsa H. Land,et al.  An Automatic Method of Solving Discrete Programming Problems , 1960 .

[21]  D. Tarlinton,et al.  Germinal centers: form and function. , 1998, Current opinion in immunology.

[22]  Vcs Vincent Wiers.  Human-computer interaction in production scheduling : analysis and design of decision support systems for production scheduling tasks , 1997 .

[23]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

[24]  N. K. Jerne,et al.  The immune system. , 1973, Scientific American.

[25]  Peter Brucker,et al.  Job-shop scheduling with multi-purpose machines , 1991, Computing.

[26]  Guan-Chun Luh,et al.  Job Shop Scheduling Optimization Using Multi-modal Immune Algorithm , 2007, IEA/AIE.

[27]  Mikkel T. Jensen,et al.  Generating robust and flexible job shop schedules using genetic algorithms , 2003, IEEE Trans. Evol. Comput..

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

[29]  Yoshiteru Ishida.  An immune network model and its applications to process diagnosis , 1993, Systems and Computers in Japan.

[30]  Peter Ross,et al.  An Immune System Approach to Scheduling in Changing Environments , 1999, GECCO.

[31]  F.J. Von Zuben,et al.  Makespan minimization on parallel processors: an immune-based approach , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[32]  Mostafa Zandieh,et al.  An artificial immune algorithm for the flexible job-shop scheduling problem , 2010, Future Gener. Comput. Syst..

[33]  Hugues Bersini,et al.  Hints for Adaptive Problem Solving Gleaned from Immune Networks , 1990, PPSN.

[34]  Hugues Bersini,et al.  The Immune Recruitment Mechanism: A Selective Evolutionary Strategy , 1991, ICGA.

[35]  Tomoyuki Miyashita,et al.  An application of immune algorithms for job-shop scheduling problems , 2003, Proceedings of the IEEE International Symposium onAssembly and Task Planning, 2003..

[36]  Jonathan Timmis,et al.  Application areas of AIS: The past, the present and the future , 2008, Appl. Soft Comput..