Performance comparison of some evolutionary algorithms on job shop scheduling problems

Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.

[1]  J. Carlier,et al.  An algorithm for solving the job-shop problem , 1989 .

[2]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[3]  C.K. Wong,et al.  Two simulated annealing-based heuristics for the job shop scheduling problem , 1999, Eur. J. Oper. Res..

[4]  Emanuela Merelli,et al.  A tabu search method guided by shifting bottleneck for the job shop scheduling problem , 2000, Eur. J. Oper. Res..

[5]  D. Y. Sha,et al.  A hybrid particle swarm optimization for job shop scheduling problem , 2006, Comput. Ind. Eng..

[6]  Mohsen Ramezani Ghalenoei,et al.  Discrete invasive weed optimization algorithm: application to cooperative multiple task assignment of UAVs , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

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

[8]  Zong Woo Geem,et al.  Optimal Scheduling of Multiple Dam System Using Harmony Search Algorithm , 2007, IWANN.

[9]  Dipankar Dasgupta,et al.  An Overview of Artificial Immune Systems and Their Applications , 1993 .

[10]  Helena Ramalhinho Dias Lourenço,et al.  Job-shop scheduling: Computational study of local search and large-step optimization methods , 1995 .

[11]  K. Lee,et al.  A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice , 2005 .

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

[13]  M. Fesanghary,et al.  Design optimization of shell and tube heat exchangers using global sensitivity analysis and harmony search algorithm , 2009 .

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

[15]  Türkay Dereli,et al.  MULTIPLE DISPATCHING RULE BASED HEURISTIC FOR MULTI-OBJECTIVE SCHEDULING OF JOB SHOPS USING TABU SEARCH , 2002 .

[16]  Javier Del Ser,et al.  On the design of a novel two-objective harmony search approach for distance- and connectivity-based localization in wireless sensor networks , 2013, Eng. Appl. Artif. Intell..

[17]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[18]  Petros Koumoutsakos,et al.  Optimization based on bacterial chemotaxis , 2002, IEEE Trans. Evol. Comput..

[19]  Z W Geem,et al.  APPLICATION OF HARMONY SEARCH TO MULTI-OBJECTIVE OPTIMIZATION FOR SATELLITE HEAT PIPE DESIGN , 2006 .

[20]  D. Dasgupta.  Artificial Immune Systems and Their Applications , 1998, Springer Berlin Heidelberg.

[21]  Saeed Zolfaghari,et al.  A comparative study of a new heuristic based on adaptive memory programming and simulated annealing: The case of job shop scheduling , 2007, Eur. J. Oper. Res..

[22]  A. A Boushaala,et al.  SOME HEURISTIC RULES FOR JOB SHOP SCHEDULING PROBLEM , 2013 .

[23]  Václav Snásel,et al.  A modified Invasive Weed Optimization algorithm for time-modulated linear antenna array synthesis , 2010, IEEE Congress on Evolutionary Computation.

[24]  M. Fesanghary,et al.  An improved harmony search algorithm for solving optimization problems , 2007, Appl. Math. Comput..

[25]  A. Mallahzadeh,et al.  Application of the Invasive Weed Optimization Technique for Antenna Configurations , 2008 .

[26]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[27]  Rosenberg J. Romero,et al.  Experimental thermodynamic evaluation for a single stage heat transformer prototype build with commercial PHEs , 2015 .

[28]  Jacek Blazewicz,et al.  The job shop scheduling problem: Conventional and new solution techniques , 1996 .

[29]  Henry Y. K. Lau,et al.  An AIS-based hybrid algorithm for static job shop scheduling problem , 2012, Journal of Intelligent Manufacturing.

[30]  Jonathan Timmis,et al.  Artificial immune systems as a novel soft computing paradigm , 2003, Soft Comput..

[31]  Václav Snásel,et al.  A Modified Invasive Weed Optimization Algorithm for training of feed- forward Neural Networks , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[32]  Yasuhiro Tsujimura,et al.  A tutorial survey of job-shop scheduling problems using genetic algorithms, part II: hybrid genetic search strategies , 1999 .