scholarly journals Production scheduling of bar mill using the combination of particle swarm optimization and Nawaz enscore ham for minimizing makespan in steel company

2019 ◽  
Author(s):  
Yusraini Muharni ◽  
Evi Febianti ◽  
Hanifa ◽  
Arlianur
Keyword(s):  
Particle Swarm Optimization ◽  
Production Scheduling ◽  
Particle Swarm ◽  
Steel Company ◽  
Swarm Optimization

scholarly journals Energy-Saving Production Scheduling in a Single-Machine Manufacturing System by Improved Particle Swarm Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Qingquan Jiang ◽  
Xiaoya Liao ◽  
Rui Zhang ◽  
Qiaozhen Lin
Keyword(s):  
Particle Swarm Optimization ◽  
Single Machine ◽  
Production Scheduling ◽  
Large Scale ◽  
Heuristic Algorithms ◽  
Particle Swarm ◽  
Total Weighted Tardiness ◽  
Production Environment ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization

A single-machine scheduling problem that minimizes the total weighted tardiness with energy consumption constraints in the actual production environment is studied in this paper. Based on the properties of the problem, an improved particle swarm optimization (PSO) algorithm embedded with a local search strategy (PSO-LS) is designed to solve this problem. To evaluate the algorithm, some computational experiments are carried out using PSO-LS, basic PSO, and a genetic algorithm (GA). Before the comparison experiment, the Taguchi method is used to select appropriate parameter values for these three algorithms since heuristic algorithms rely heavily on their parameters. The experimental results show that the improved PSO-LS algorithm has considerable advantages over the basic PSO and GA, especially for large-scale problems.

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