Differential Evolution Based Hyper-heuristic for the Flexible Job-Shop Scheduling Problem with Fuzzy Processing Time

In this paper, a differential evolution based hyper-heuristic (DEHH) algorithm is proposed to solve the flexible job-shop scheduling problem with fuzzy processing time (FJSPF). In the DEHH scheme, five simple and effective heuristic rules are designed to construct a set of low-level heuristics, and differential evolution is employed as the high-level strategy to manipulate the low-level heuristics to operate on the solution domain. Additionally, an efficient hybrid machine assignment scheme is proposed to decode a solution to a feasible schedule. The effectiveness of the DEHH is evaluated on two typical benchmark sets and the computational results indicate the superiority of the proposed hyper-heuristic scheme over the state-of-the-art algorithms.

[1]  Deming Lei,et al.  A genetic algorithm for flexible job shop scheduling with fuzzy processing time , 2010 .

[2]  Sancho Salcedo-Sanz,et al.  An evolutionary-based hyper-heuristic approach for the Jawbreaker puzzle , 2013, Applied Intelligence.

[3]  Hua Xu,et al.  Flexible job shop scheduling using hybrid differential evolution algorithms , 2013, Comput. Ind. Eng..

[4]  Mohsen Ziaee,et al.  A heuristic algorithm for solving flexible job shop scheduling problem , 2014 .

[5]  Shengyao Wang,et al.  An effective artificial bee colony algorithm for the flexible job-shop scheduling problem , 2012 .

[6]  Min Liu,et al.  A hybrid artificial bee colony algorithm for the fuzzy flexible job-shop scheduling problem , 2013 .

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

[8]  Iván García-Magariño,et al.  Modular design of a hybrid genetic algorithm for a flexible job-shop scheduling problem , 2011, Knowl. Based Syst..

[9]  Mehmet Fatih Tasgetiren,et al.  An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time , 2015 .

[10]  Jian Lin,et al.  A backtracking search hyper-heuristic for the distributed assembly flow-shop scheduling problem , 2017, Swarm Evol. Comput..

[11]  M.C. Gomes *,et al.  Optimal scheduling for flexible job shop operation , 2005 .

[12]  Inderveer Chana,et al.  Bacterial foraging based hyper-heuristic for resource scheduling in grid computing , 2013, Future Gener. Comput. Syst..

[13]  Sanja Petrovic,et al.  A cooperative hyper-heuristic search framework , 2010, J. Heuristics.

[14]  Konstantinos P. Anagnostopoulos,et al.  A particle swarm optimization based hyper-heuristic algorithm for the classic resource constrained project scheduling problem , 2014, Inf. Sci..

[15]  Sancho Salcedo-Sanz,et al.  An evolutionary-based hyper-heuristic approach for optimal construction of group method of data handling networks , 2013, Inf. Sci..

[16]  Patrick Siarry,et al.  Biogeography-based optimization for constrained optimization problems , 2012, Comput. Oper. Res..

[17]  Haoxun Chen,et al.  A genetic algorithm for flexible job-shop scheduling , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[18]  Shengyao Wang,et al.  An effective estimation of distribution algorithm for the flexible job-shop scheduling problem with fuzzy processing time , 2013 .

[19]  Ye Xu,et al.  An effective teaching-learning-based optimization algorithm for the flexible job-shop scheduling problem with fuzzy processing time , 2015, Neurocomputing.

[20]  G. Bortolan,et al.  A review of some methods for ranking fuzzy subsets , 1985 .

[21]  Mohammad Saidi-Mehrabad,et al.  Flexible job shop scheduling with tabu search algorithms , 2007 .

[22]  Emma Hart,et al.  A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling , 2016, Evolutionary Computation.

[23]  Mostafa Zandieh,et al.  An efficient knowledge-based algorithm for the flexible job shop scheduling problem , 2012, Knowl. Based Syst..

[24]  Jian Lin,et al.  A hybrid biogeography-based optimization for the fuzzy flexible job-shop scheduling problem , 2015, Knowl. Based Syst..

[25]  K. Anwar,et al.  Harmony Search-based Hyper-heuristic for examination timetabling , 2013, 2013 IEEE 9th International Colloquium on Signal Processing and its Applications.

[26]  Rasaratnam Logendran,et al.  A Tabu search-based approach for scheduling job-shop type flexible manufacturing systems , 1997 .

[27]  Quan-Ke Pan,et al.  An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time , 2016, Expert Syst. Appl..

[28]  P. N. Suganthan,et al.  Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.

[29]  Deming Lei,et al.  Co-evolutionary genetic algorithm for fuzzy flexible job shop scheduling , 2012, Appl. Soft Comput..

[30]  Andrea Rossi,et al.  Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships , 2014 .

[31]  Mostafa Zandieh,et al.  Integrating simulation and genetic algorithm to schedule a dynamic flexible job shop , 2009, J. Intell. Manuf..

[32]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[33]  Mitsuo Gen,et al.  A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems , 2008, Comput. Oper. Res..

[34]  Masatoshi Sakawa,et al.  Fuzzy programming for multiobjective job shop scheduling with fuzzy processing time and fuzzy duedate through genetic algorithms , 2000, Eur. J. Oper. Res..