A hybrid discrete firefly algorithm for solving multi-objective flexible job shop scheduling problems

Firefly algorithm FA is a nature-inspired optimisation algorithm that can be successfully applied to continuous optimisation problems. However, lot of practical problems are formulated as discrete optimisation problems. In this paper a hybrid discrete firefly algorithm HDFA is proposed to solve the multi-objective flexible job shop scheduling problem FJSP. FJSP is an extension of the classical job shop scheduling problem that allows an operation to be processed by any machine from a given set along different routes. Three minimisation objectives - the maximum completion time, the workload of the critical machine and the total workload of all machines are considered simultaneously. This paper also proposes firefly algorithms discretisation which consists of constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. In the proposed algorithm discrete firefly algorithm DFA is combined with local search LS method to enhance the searching accuracy and information sharing among fireflies. The experimental results on the well-known benchmark instances and comparison with other recently published algorithms shows that the proposed algorithm is feasible and an effective approach for the multi-objective flexible job shop scheduling problems.

[1]  S. Karthikeyan,et al.  Solving flexible job-shop scheduling problem using hybrid particle swarm optimisation algorithm and data mining , 2012, Int. J. Manuf. Technol. Manag..

[2]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[3]  Slawomir Zak,et al.  Firefly Algorithm for Continuous Constrained Optimization Tasks , 2009, ICCCI.

[4]  Mohammad Kazem Sayadia,et al.  A discrete firefly metaheuristic with local search for makespan minimization in permutation flow shop scheduling problems , 2010 .

[5]  Peigen Li,et al.  A tabu search algorithm with a new neighborhood structure for the job shop scheduling problem , 2007, Comput. Oper. Res..

[6]  Xin-She Yang,et al.  Bat algorithm: literature review and applications , 2013, Int. J. Bio Inspired Comput..

[7]  Felix T.S. Chan,et al.  Flexible job-shop scheduling problem under resource constraints , 2006 .

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

[9]  Li-Ning Xing,et al.  An efficient search method for multi-objective flexible job shop scheduling problems , 2009, J. Intell. Manuf..

[10]  Xin-She Yang,et al.  A Discrete Firefly Algorithm for the Multi-Objective Hybrid Flowshop Scheduling Problems , 2014, IEEE Transactions on Evolutionary Computation.

[11]  Imed Kacem,et al.  Genetic algorithm for the flexible job-shop scheduling problem , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[12]  Nidhal Rezg,et al.  An integrated greedy heuristic for a flexible job shop scheduling problem , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).

[13]  Fernando A. Tohmé,et al.  A memetic algorithm based on a NSGAII scheme for the flexible job-shop scheduling problem , 2010, Ann. Oper. Res..

[14]  Juan Luis Fernández-Martínez,et al.  A Brief Historical Review of Particle Swarm Optimization (PSO) , 2012 .

[15]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[16]  Liang Gao,et al.  An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem , 2009, Comput. Ind. Eng..

[17]  Mauro Dell'Amico,et al.  Applying tabu search to the job-shop scheduling problem , 1993, Ann. Oper. Res..

[18]  G. Moslehi,et al.  A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search , 2011 .

[19]  Pierre Borne,et al.  Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic , 2002, Math. Comput. Simul..

[20]  S. GirishB.,et al.  A particle swarm optimization algorithm for flexible job shop scheduling problem , 2009, 2009 IEEE International Conference on Automation Science and Engineering.

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

[22]  Sheik Meeran,et al.  Deterministic job-shop scheduling: Past, present and future , 1999, Eur. J. Oper. Res..

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

[24]  Quan-Ke Pan,et al.  An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems , 2010, Comput. Ind. Eng..

[25]  Li-Ning Xing,et al.  Multi-objective flexible job shop schedule: Design and evaluation by simulation modeling , 2009, Appl. Soft Comput..

[26]  J. Chen,et al.  A hybrid Pareto-based local search algorithm for multi-objective flexible job shop scheduling problems , 2012 .

[27]  Vinícius Amaral Armentano,et al.  Tardiness minimization in a flexible job shop: A tabu search approach , 2004, J. Intell. Manuf..

[28]  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.

[29]  Quan-Ke Pan,et al.  An effective shuffled frog-leaping algorithm for multi-objective flexible job shop scheduling problems , 2012, Appl. Math. Comput..

[30]  Ravi Sethi,et al.  The Complexity of Flowshop and Jobshop Scheduling , 1976, Math. Oper. Res..

[31]  M. Sayadi,et al.  A discrete firefly meta-heuristic with local search for makespan minimization in permutation flow shop scheduling problems , 2010 .

[32]  E. Nowicki,et al.  A Fast Taboo Search Algorithm for the Job Shop Problem , 1996 .

[33]  X. Shao,et al.  A multi-objective genetic algorithm based on immune and entropy principle for flexible job-shop scheduling problem , 2010 .

[34]  N. Jawahar,et al.  A particle swarm optimization algorithm for flexible jobshop scheduling problem , 2009, CASE 2009.

[35]  Yi Pan,et al.  An efficient flow-shop scheduling algorithm based on a hybrid particle swarm optimization model , 2009, Expert Syst. Appl..

[36]  Amrit Pal Singh,et al.  Comparative Study of Firefly Algorithm and Particle Swarm Optimization for Noisy Non- Linear Optimization Problems , 2012 .

[37]  Tsung-Che Chiang,et al.  A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling , 2013 .

[38]  Thatchai Thepphakorn,et al.  Application of Firefly Algorithm and Its Parameter Setting for Job Shop Scheduling , 2012 .

[39]  Zhihua Cui,et al.  Artificial Plant Optimization Algorithm with Correlation Branches , 2013 .

[40]  Quan-Ke Pan,et al.  Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems , 2011 .

[41]  Zhiming Wu,et al.  An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems , 2005, Comput. Ind. Eng..

[42]  Suyanto,et al.  Evolutionary Discrete Firefly Algorithm for Travelling Salesman Problem , 2011, ICAIS.

[43]  Rémy Dupas,et al.  Evaluation of mutation heuristics for solving a multiobjective flexible job shop by an evolutionary algorithm , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[44]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[45]  Andrzej Jaszkiewicz,et al.  Pareto Simulated Annealing for Fuzzy Multi-Objective Combinatorial Optimization , 2000, J. Heuristics.

[46]  Nhu Binh Ho,et al.  An effective architecture for learning and evolving flexible job-shop schedules , 2007, Eur. J. Oper. Res..

[47]  Paolo Brandimarte,et al.  Routing and scheduling in a flexible job shop by tabu search , 1993, Ann. Oper. Res..