A hybrid metaheuristic model for job shop rescheduling problem

This paper discusses on developing a hybrid metaheuristic model to tackle the problem of changing environment in the job shop scheduling problem.The main idea is to use the model to develop building blocks of partial schedules that can be used to provide backup solutions when disturbances occur during production.Each partial schedule is assigned a fitness value for the selection of final population of best partial schedules.The results of the experiments show an improvement from a previous work. Future work on this study is also discussed.

[1]  Peter Ross,et al.  The evolution and analysis of potential antibody library for use in job-shop scheduling , 1999 .

[2]  Upendra Dave,et al.  Heuristic Scheduling Systems , 1993 .

[3]  Edmund K. Burke,et al.  A Multi-Start Very Large Neighbourhood Search Approach with Local Search Methods for Examination Timetabling , 2006, ICAPS.

[4]  Tim Kovacs,et al.  On the contribution of gene libraries to artificial immune systems , 2005, GECCO '05.

[5]  Kathryn A. Dowsland,et al.  Off-the-Peg or Made-to-Measure? Timetabling and Scheduling with SA and TS , 1997, PATAT.

[6]  Alan S. Perelson,et al.  The Evolution of Emergent Organization in Immune System Gene Libraries , 1995, ICGA.

[7]  Hedieh Sajedi,et al.  A Novel Artificial Immune Algorithm for Solving the Job Shop Scheduling Problem , 2012 .

[8]  Yuping Wang,et al.  A new hybrid genetic algorithm for job shop scheduling problem , 2012, Comput. Oper. Res..

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

[10]  Jonathan Timmis,et al.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[11]  F. Glover,et al.  In Modern Heuristic Techniques for Combinatorial Problems , 1993 .

[12]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[13]  Xueni Qiu,et al.  A Hybrid AIS-based Algorithm for Solving Job Shop Scheduling Problem , 2012, 2012 International Conference on Communication Systems and Network Technologies.

[14]  Haibo Hu,et al.  Hybrid Artificial Immune System for Job Shop Scheduling Problem , 2011 .

[15]  Yanchun Liang,et al.  Solving Job-Shop Scheduling Problems by a Novel Artificial Immune System , 2005, Australian Conference on Artificial Intelligence.

[16]  Carlos A. Coello Coello,et al.  Use of an Artificial Immune System for Job Shop Scheduling , 2003, ICARIS.

[17]  Peter Ross,et al.  A Promising Genetic Algorithm Approach to Job-Shop SchedulingRe-Schedulingand Open-Shop Scheduling Problems , 1993, ICGA.

[18]  Jan Korst,et al.  Chapter 7 SIMULATED ANNEALING , 2007 .

[19]  G. Dueck.  New optimization heuristics , 1993 .

[20]  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).

[21]  L. Sompayrac,et al.  How the immune system works , 1999 .

[22]  Alper Döyen,et al.  A new approach to solve hybrid flow shop scheduling problems by artificial immune system , 2004, Future Gener. Comput. Syst..

[23]  Mihaela Oprea,et al.  Simulated evolution of antibody gene libraries under pathogen selection , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

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

[25]  Kathryn A. Dowsland,et al.  General Cooling Schedules for a Simulated Annealing Based Timetabling System , 1995, PATAT.

[26]  Sanja Petrovic,et al.  A time-predefined local search approach to exam timetabling problems , 2004 .

[27]  M. Chandrasekaran,et al.  Solving job shop scheduling problems using artificial immune system , 2006 .

[28]  Edmund K. Burke,et al.  Practice and Theory of Automated Timetabling II , 1997, Lecture Notes in Computer Science.