Parallel Simulated Annealing for the Job Shop Scheduling Problem

This paper describes two parallel simulated annealing algorithms for the job shop scheduling problem with the sum of job completion times criterion. Some properties of the problem associated with the block theory have been presented and discussed. These properties allow us to introduce the effective neighborhood based on the adjacent swap type moves. In this paper, an original method for parallel calculation of optimization criterion value for set of solutions, recommended for the use in metaheuristics with single- and multiple- search trajectories is proposed. Additionally, the vector calculation method, that uses multiple mathematical instructions MMX supported by suitable data organization, is presented. Properties of parallel calculations are empirically verified on the PC with Intel Core 2 Duo processor on Taillard's benchmarks.

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

[2]  T. Yamada,et al.  Solving the C/sub sum/ permutation flowshop scheduling problem by genetic local search , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[3]  M. Inés Torres,et al.  Pattern recognition and applications , 2000 .

[4]  Joseph A. Svestka,et al.  A bi-directional scheduling approach for job shops , 1999 .

[5]  Eugeniusz Nowicki,et al.  An Advanced Tabu Search Algorithm for the Job Shop Problem , 2005, J. Sched..

[6]  Éric D. Taillard,et al.  Benchmarks for basic scheduling problems , 1993 .

[7]  Ramesh Sharda,et al.  Metaheuristic Optimization via Memory and Evolution , 2005 .

[8]  Sheik Meeran,et al.  New and “Stronger” Job-Shop Neighbourhoods: A Focus on the Method of Nowicki and Smutnicki (1996) , 2000, J. Heuristics.

[9]  Chandrasekharan Rajendran,et al.  Efficient jobshop dispatching rules: Further developments , 2000 .

[10]  Kuei-Bin Wu,et al.  An efficient configuration generation mechanism to solve job shop scheduling problems by the simulated annealing algorithm , 1999, Int. J. Syst. Sci..

[11]  Mieczysław Wodecki,et al.  A Very Fast Tabu Search Algorithm for Job Shop Problem , 2005 .

[12]  Christian Bierwirth,et al.  An efficient genetic algorithm for job shop scheduling with tardiness objectives , 2004, Eur. J. Oper. Res..

[13]  Emile H. L. Aarts,et al.  Simulated annealing: A pedestrian review of the theory and some applications , 1987 .

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

[15]  Taeyong Yang,et al.  An exchange heuristic imbedded with simulated annealing for due-dates job-shop scheduling , 1996 .

[16]  Vinicius Amaral Armentano,et al.  Tabu search for minimizing total tardiness in a job shop , 2000 .