Control Systems and Computers, N5, 2019, Article 5

https://doi.org/10.15407/csc.2019.05.039

Control Systems and Computers, 2019, Issue 5 (283), pp. 39-47.

UDK 658.5

Tadeush Witkowski, Faculty of Production Engineering, Warsaw University of Technology, Plac Politechniki, 1, 00-661, Warsaw, Poland,Warsaw, Poland

The DABC and TLBO Algorithms for Solve Job Shop Scheduling Problem

This paper shows use Discrete Artificial Bee Colony and Teaching-Learning-Based Optimization algorithms for solving the job shop scheduling problem in order to minimize makespan (Cmax value). The Job Shop Scheduling Problem is one of the most difficult problems as it is classified as an NP-hard one. Stochastic search techniques, such as evolutionary algorithms, are used to find a good solution. Our objective is to estimate efficiency of Discrete Artificial Bee Colony and Teaching-Learning-Based Optimization algorithms on many tests of job shop scheduling problem.

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Keywords: Discrete Artificial Bee Colony Algorithm; Teaching-Learning-Based Optimization; job shop scheduling problem;  makespan

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Received 10.10.2019