scholarly journals An Efficient Simulated Annealing Algorithm for a No-Wait Two Stage Flexible Flow Shop Scheduling Problem

2011 ◽  
Author(s):  
Meysam Rabiee ◽  
Pezhman Ramezani ◽  
Rasoul Shafaei
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Two Stage ◽  
Shop Scheduling ◽  
Annealing Algorithm ◽  
No Wait ◽  
Flexible Flow Shop Scheduling

scholarly journals Flexible Flow Shop Scheduling Method with Public Buffer

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 681
Author(s):  
Han ◽  
Han ◽  
Lin ◽  
Dong ◽  
Shi
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Flexible Flow Shop ◽  
The Public ◽  
Shop Scheduling ◽  
Annealing Algorithm ◽  
Flexible Flow Shop Scheduling ◽  
Local Scheduling

Actual manufacturing enterprises usually solve the production blockage problem by increasing the public buffer. However, the increase of the public buffer makes the flexible flow shop scheduling rather challenging. In order to solve the flexible flow shop scheduling problem with public buffer (FFSP–PB), this study proposes a novel method combining the simulated annealing algorithm-based Hopfield neural network algorithm (SAA–HNN) and local scheduling rules. The SAA–HNN algorithm is used as the global optimization method, and constructs the energy function of FFSP–PB to apply its asymptotically stable characteristic. Due to the limitations, such as small search range and high probability of falling into local extremum, this algorithm introduces the simulated annealing algorithm idea such that the algorithm is able to accept poor fitness solution and further expand its search scope during asymptotic convergence. In the process of local scheduling, considering the transferring time of workpieces moving into and out of public buffer and the manufacturing state of workpieces in the production process, this study designed serval local scheduling rules to control the moving process of the workpieces between the public buffer and the limited buffer between the stages. These local scheduling rules can also be used to reduce the production blockage and improve the efficiency of the workpiece transfer. Evaluated by the groups of simulation schemes with the actual production data of one bus manufacturing enterprise, the proposed method outperforms other methods in terms of searching efficiency and optimization target.

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.

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