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Improving the TSAB algorithm through parallel computing

Rudy Jarosław, Pempera Jaroslaw, Smutnicki Czesław

Archives of Control Sciences

2020

Vol. 30, No. 3

411--435

In this paper, a parallel multi-path variant of the well-known TSAB algorithm for the job shop scheduling problem is proposed. Coarse-grained parallelization method is employed, which allows for great scalability of the algorithm with accordance to Gustafon’s law. The resulting P-TSAB algorithm is tested using 162 well-known literature benchmarks. Results indicate that P-TSAB algorithm with a running time of one minute on a modern PC provides solutions comparable to the ones provided by the newest literature approaches to the job shop scheduling problem. Moreover, on average P-TSAB achieves two times smaller percentage relative deviation from the best known solutions than the standard variant of TSAB. The use of parallelization also relieves the user from having to fine-tune the algorithm. The P-TSAB algorithm can thus beused as module in real-life production planning systems or as a local search procedure in other algorithms. It can also provide the upper bound of minimal cycle time for certain problems of cyclic scheduling.

Optimization of production process for resource utilization

Bozejko Wojciech, Burduk Anna, Pempera Jaroslaw, Wodecki Mieczysław

Archives of Civil and Mechanical Engineering

2019

Vol. 19, no. 4

1251--1258

The paper presents a method of scheduling execution of technological operations in work centres in a company manufacturing seats for passenger cars. To that end, an optimization algorithm based on the B&B method was developed, aimed at minimizing the number of employees necessary for operation of the work centres and at maximizing capacity of the manufacturing process. Efficiency and effectiveness of the algorithm was verified on the grounds of real data coming from the manufacturing company.