A New Mathematical Model for Fuzzy Flexible Flow Shop Scheduling of Unrelated Parallel Machines Maximizing the Weighted Satisfaction Level

2009 ◽  
Author(s):  
Tavakkoli-Moghaddam, Reza
Keyword(s):  
Mathematical Model ◽  
Parallel Machines ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Satisfaction Level ◽  
Unrelated Parallel Machines ◽  
Flexible Flow Shop ◽  
Shop Scheduling ◽  
Flexible Flow Shop Scheduling

scholarly journals Solving no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines and rework time by the adjusted discrete Multi Objective Invasive Weed Optimization and fuzzy dominance approach

2017 ◽  
Vol 10 (5) ◽  
pp. 887 ◽  
Author(s):  
Hassan Jafarzadeh ◽  
Nazanin Moradinasab ◽  
Ali Gerami
Keyword(s):  
Parallel Machines ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Two Stage ◽  
Flexible Flow Shop ◽  
Shop Scheduling ◽  
Multi Objective ◽  
No Wait ◽  
Flexible Flow Shop Scheduling

Purpose: Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem.Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm.Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm.Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.

An efficiency improvement of flexible flow shop scheduling in automotive part company

2020 ◽  
pp. 1-14
Author(s):  
Waraporn Fangrit ◽  
Hwa Jen Yap ◽  
Mukhtar Fatihu Hamza ◽  
Siow-Wee Chang ◽  
Keem Siah Yap ◽  
...  
Keyword(s):  
Tabu Search ◽  
Flow Shop ◽  
Simulation Software ◽  
Flow Shop Scheduling ◽  
Current Status ◽  
Flexible Flow Shop ◽  
Shop Scheduling ◽  
Scheduling Method ◽  
Automotive Part ◽  
Flexible Flow Shop Scheduling

Flexible flow shop is becoming more interested and applied in industries due to its impact from higher workloads. Flexible flow shop scheduling problem is focused to minimize the makespan. A metaheuristic model based on Hybrid Tabu Search is developed to overcome this problem. Firstly, Hybrid Tabu Search is modelled based on the factory data. The Earliest Due Date rule is used as the scheduling method for the current status. FlexSim simulation software is used to evaluate the Hybrid Tabu Search model. The outcome is validated with two different basic heuristic solutions; Campbell, Dudek and Smith’s and Gupta’s heuristics. It is found that the proposed model can improve the job sequence based on makespan criteria.

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