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 | ||
| Author | ||
| Wael Mohamed Fawaz Abdel-Rehim* | ||
| 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 | ||
|
Statistics Article View: 162 PDF Download: 156 |
||
