Implementation of a Binary Kidney-Inspired Algorithm Based on a Parallel Method for Solving the Job Shop Scheduling Problem | ||||
| Frontiers in Scientific Research and Technology | ||||
| Volume 7, Issue 1, December 2023 PDF (394.03 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/fsrt.2023.234065.1106 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Wael Mohamed Fawaz Abdel-Rehim  
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| Computer Science Department, Faculty of Computers and Information, Suez University, Suez, Egypt | ||||
| Abstract | ||||
| This paper proposes a binary kidney-inspired algorithm (KA) to tackle the job shop scheduling problem (JSSP), and its solution is essential in manufacturing, especially in real industrial engineering. The job shop scheduling problem is a computer science optimization problem, and it is among the most significant and challenging issues in the field of production scheduling. The proposed algorithm is based on a parallel method with many threads. This algorithm is checked using certain job shop benchmark problems. The findings are compared with those retrieved using two techniques: a genetic algorithm (GA) and a particle swarm optimization (PSO) method. These techniques indicate that applying the binary kidney-inspired in parallel is an efficient algorithm for solving the JSSP, shows remarkable competitiveness, and considerably accelerates speedups, especially in large-scale instances. The achieved results are based on four threads; the speedup is 3.13 for the FT06 instance, while the execution time is 2.24 seconds. | ||||
| Keywords | ||||
| Job Shop Scheduling Problem (JSSP); Optimization, MATLAB; Meta-heuristics; Kidney-inspired algorithm | ||||
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