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.
Abdel-Rehim, W. (2023). 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, 7(1), -. doi: 10.21608/fsrt.2023.234065.1106
MLA
Wael Mohamed Fawaz Abdel-Rehim. "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, 7, 1, 2023, -. doi: 10.21608/fsrt.2023.234065.1106
HARVARD
Abdel-Rehim, W. (2023). '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, 7(1), pp. -. doi: 10.21608/fsrt.2023.234065.1106
VANCOUVER
Abdel-Rehim, W. 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, 2023; 7(1): -. doi: 10.21608/fsrt.2023.234065.1106