Handling ties in heuristics for the permutation flow shop scheduling problem

Abstract The NEH heuristic, as the most efficient procedure for the flow shop scheduling problem is based on constructing a sequence of jobs by iteratively inserting the non-scheduled jobs into a current subsequence. The initial phase of NEH, in which an initial order (priority order) of jobs is defined, and the insertion procedure, usually cause a high number of ties. Unlike the sort of ties in the insertion phase, the ties in the initial phase are not uniquely defined by the definition of NEH. This results in an inaccuracy in most of the large number of published experimental results on this topic. The experimental research, presented in this paper confirms the importance of the inclusion of the information about the sort of ties in the initial phase in any experimental result related to NEH. The conclusion, obtained by this study, is that the range of the objective values for different sorts of ties is often greater than the improvements, published in literature. This allowed us to construct a very simple algorithm that outperforms published NEH improvements, maintaining NEH's exceptional efficiency. The proposed algorithm also uses the information about the ties in the insertion phase to improve the objective value. The permutation flow shop problem primarily concerns the makespan objective, but the main conclusions can be applied to other flow shop problems as well.

[1]  Chandrasekharan Rajendran,et al.  Performance evaluation of priority dispatching rules in multi-level assembly job shops with jobs having weights for flowtime and tardiness , 2006 .

[2]  J. Kamburowski,et al.  On the NEH heuristic for minimizing the makespan in permutation flow shops , 2007 .

[3]  Mieczysław Wodecki,et al.  A very fast tabu search algorithm for the permutation flow shop problem with makespan criterion , 2004, Comput. Oper. Res..

[4]  C. Rajendran,et al.  Different initial sequences for the heuristic of Nawaz, Enscore and Ham to minimize makespan, idletime or flowtime in the static permutation flowshop sequencing problem , 2003 .

[5]  É. Taillard Some efficient heuristic methods for the flow shop sequencing problem , 1990 .

[6]  Thomas Stützle,et al.  A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem , 2007, Eur. J. Oper. Res..

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

[8]  Shiji Song,et al.  An improved version of the NEH algorithm and its application to large-scale flow-shop scheduling problems , 2007 .

[9]  Bo Liu,et al.  An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[10]  Dipak Laha,et al.  Improved heuristically guided genetic algorithm for the flow shop scheduling problem , 2007 .

[11]  Ping Chen,et al.  An improved NEH-based heuristic for the permutation flowshop problem , 2008, Comput. Oper. Res..

[12]  L. Darrell Whitley,et al.  Contrasting Structured and Random Permutation Flow-Shop Scheduling Problems: Search-Space Topology and Algorithm Performance , 2002, INFORMS J. Comput..

[13]  Anurag Agarwal,et al.  Improvement heuristic for the flow-shop scheduling problem: An adaptive-learning approach , 2006, Eur. J. Oper. Res..

[14]  Pin Luarn,et al.  A discrete version of particle swarm optimization for flowshop scheduling problems , 2007, Comput. Oper. Res..

[15]  Xavier Tort-Martorell,et al.  Comparing three-step heuristics for the permutation flow shop problem , 2010, Comput. Oper. Res..

[16]  Jerzy Kamburowski,et al.  On Recent Modifications And Extensions Of The Neh Heuristic For Flow Shop Sequencing , 2011 .

[17]  Jose M. Framiñan,et al.  A review and classification of heuristics for permutation flow-shop scheduling with makespan objective , 2004, J. Oper. Res. Soc..

[18]  Godfrey C. Onwubolu,et al.  Scheduling flow shops using differential evolution algorithm , 2006, Eur. J. Oper. Res..

[19]  Mehmet Fatih Tasgetiren,et al.  A discrete differential evolution algorithm for the permutation flowshop scheduling problem , 2007, GECCO '07.

[20]  Victor Fernandez-Viagas,et al.  On insertion tie-breaking rules in heuristics for the permutation flowshop scheduling problem , 2014, Comput. Oper. Res..

[21]  Jerzy Kamburowski,et al.  An improved NEH heuristic to minimize makespan in permutation flow shops , 2008, Comput. Oper. Res..

[22]  Inyong Ham,et al.  A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem , 1983 .

[23]  S. M. Johnson,et al.  Optimal two- and three-stage production schedules with setup times included , 1954 .

[24]  Ping Chen,et al.  A More Effective Constructive Algorithm for Permutation Flowshop Problem , 2006, IDEAL.

[25]  E. Nowicki,et al.  A fast tabu search algorithm for the permutation flow-shop problem , 1996 .

[26]  Burak Eksioglu,et al.  A tabu search algorithm for the flowshop scheduling problem with changing neighborhoods , 2008, Comput. Ind. Eng..

[27]  Rubén Ruiz,et al.  A comprehensive review and evaluation of permutation flowshop heuristics to minimize flowtime , 2013, Comput. Oper. Res..

[28]  Jose M. Framiñan,et al.  Comparison of heuristics for flowtime minimisation in permutation flowshops Technical report IO-2003 / 01 Version 0 . 5 Last version : 26 / 07 / 2003 , 2004 .

[29]  Ping Chen,et al.  A multi-restart iterated local search algorithm for the permutation flow shop problem minimizing total flow time , 2013, Comput. Oper. Res..

[30]  Jung Woo Jung,et al.  Flowshop-scheduling problems with makespan criterion: a review , 2005 .

[31]  Bassem Jarboui,et al.  A combinatorial particle swarm optimisation for solving permutation flowshop problems , 2008, Comput. Ind. Eng..

[32]  Mehmet Fatih Tasgetiren,et al.  A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem , 2007, Eur. J. Oper. Res..

[33]  A. Kan Machine Scheduling Problems: Classification, Complexity and Computations , 1976 .

[34]  Jatinder N. D. Gupta,et al.  Flowshop scheduling research after five decades , 2006, Eur. J. Oper. Res..

[35]  Pierre Hansen,et al.  Variable neighborhood search: Principles and applications , 1998, Eur. J. Oper. Res..