An Ant Colony System Algorithm for the Hybrid Flow-Shop Scheduling Problem

2011 ◽  
Vol 2 (1) ◽  
pp. 29-43 ◽  
Author(s):  
Safa Khalouli ◽  
Fatima Ghedjati ◽  
Abdelaziz Hamzaoui
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Flow Shop ◽  
Ant Colony ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Scheduling Problem ◽  
Ant Colony Optimization Algorithm ◽  
Shop Scheduling ◽  
Hybrid Flow Shop Scheduling

An integrated ant colony optimization algorithm (IACS-HFS) is proposed for a multistage hybrid flow-shop scheduling problem. The objective of scheduling is the minimization of the makespan. To solve this NP-hard problem, the IACS-HFS considers the assignment and sequencing sub-problems simultaneously in the construction procedures. The performance of the algorithm is evaluated by numerical experiments on benchmark problems taken from the literature. The results show that the proposed ant colony optimization algorithm gives promising and good results and outperforms some current approaches in the quality of schedules.

An Ant Colony System Algorithm for the Hybrid Flow-Shop Scheduling Problem

2012 ◽  
pp. 85-98
Author(s):  
Safa Khalouli ◽  
Fatima Ghedjati ◽  
Abdelaziz Hamzaoui
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Flow Shop ◽  
Ant Colony ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Scheduling Problem ◽  
Ant Colony Optimization Algorithm ◽  
Shop Scheduling ◽  
Hybrid Flow Shop Scheduling

An integrated ant colony optimization algorithm (IACS-HFS) is proposed for a multistage hybrid flow-shop scheduling problem. The objective of scheduling is the minimization of the makespan. To solve this NP-hard problem, the IACS-HFS considers the assignment and sequencing sub-problems simultaneously in the construction procedures. The performance of the algorithm is evaluated by numerical experiments on benchmark problems taken from the literature. The results show that the proposed ant colony optimization algorithm gives promising and good results and outperforms some current approaches in the quality of schedules.

scholarly journals An Improved Migrating Birds Optimization Algorithm for a Hybrid Flow Shop Scheduling within Steel Plants

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1661
Author(s):  
Dayong Han ◽  
Qiuhua Tang ◽  
Zikai Zhang ◽  
Zixiang Li
Keyword(s):  
Continuous Casting ◽  
Optimization Algorithm ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Scheduling Problem ◽  
Shop Scheduling ◽  
Hybrid Flow Shop Scheduling ◽  
Migrating Birds Optimization ◽  
Migrating Birds

Steelmaking and the continuous-casting (SCC) scheduling problem is a realistic hybrid flow shop scheduling problem with continuous-casting production at the last stage. This study considers the SCC scheduling problem with diverse products, which is a vital and difficult problem in steel plants. To tackle this problem, this study first presents the mixed-integer linear programming (MILP) model to minimize the objective of makespan. Then, an improved migrating birds optimization algorithm (IMBO) is proposed to tackle this considered NP-hard problem. In the proposed IMBO, several improvements are employed to achieve the proper balance between exploration and exploitation. Specifically, a two-level decoding procedure is designed to achieve feasible solutions; the simulated annealing-based acceptance criterion is employed to ensure the diversity of the population and help the algorithm to escape from being trapped in local optima; a competitive mechanism is developed to emphasize exploitation capacity by searching around the most promising solution space. The computational experiments demonstrate that the proposed IMBO obtains competing performance and it outperforms seven other implemented algorithms in the comparative study.

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