A simulation–optimization model for solving flexible flow shop scheduling problems with rework and transportation

2021 ◽  
Vol 180 ◽  
pp. 152-178
Author(s):  
Elmira Gheisariha ◽  
Madjid Tavana ◽  
Fariborz Jolai ◽  
Meysam Rabiee
Keyword(s):  
Optimization Model ◽  
Flow Shop ◽  
Simulation Optimization ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Flexible Flow Shop ◽  
Shop Scheduling ◽  
Flexible Flow Shop Scheduling

Flexible flow shop scheduling with interval grey processing time

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yuquan Wang ◽  
Naiming Xie
Keyword(s):  
Processing Time ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Flexible Flow Shop ◽  
Content Type ◽  
Shop Scheduling ◽  
Scheduling Model ◽  
Grey Number ◽  
Flexible Flow Shop Scheduling

Purposepurpose of this paper is providing a solution for flexible flow shop scheduling problem with uncertain processing time in aeronautical composite lay-up workshop.Design/methodology/approachA flexible flow scheduling model and algorithm with interval grey processing time is established. First, according to actual needs of composite laminate shop scheduling process, interval grey number is used to represent uncertain processing time, and interval grey processing time measurement method, grey number calculation and comparison rules, grey Gantt chart, and other methods are further applied. Then a flexible flow shop scheduling model with interval grey processing time (G-FFSP) is established, and an artificial bee colony algorithm based on an adaptive neighbourhood search strategy is designed to solve the model. Finally, six examples are generated for simulation scheduling, and the efficiency and performance of the model and algorithm are evaluated by comparing the results.FindingsResults show that flexible flow shop scheduling model and algorithm with interval grey processing time can provide an optimal solution for composite lay-up shop scheduling problems and other similar flow shop scheduling problems.Social implicationsUncertain processing time is common in flexible workshop manufacturing, and manual scheduling greatly restricts the production efficiency of workshop. In this paper, combined with grey system theory, an intelligent algorithm is used to solve flexible flow shop scheduling problem to promote intelligent and efficient production of enterprises.Originality/valueThis paper applies and perfects interval grey processing time measurement method, grey number calculation and comparison rules, grey Gantt chart and other methods. A flexible flow shop scheduling model with interval grey processing time is established, and an artificial bee colony algorithm with an adaptive domain search strategy is designed. It provides a comprehensive solution for flexible flow shop scheduling with uncertain processing time.

scholarly journals Clarifying Cutting and Sewing Processes with Due Windows Using an Effective Ant Colony Optimization

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Rong-Hwa Huang ◽  
Shun-Chi Yu
Keyword(s):  
Ant Colony Optimization ◽  
Flow Shop ◽  
Pso Algorithm ◽  
Ant Colony ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Two Stage ◽  
Flexible Flow Shop ◽  
Shop Scheduling ◽  
Flexible Flow Shop Scheduling

The cutting and sewing process is a traditional flow shop scheduling problem in the real world. This two-stage flexible flow shop is often commonly associated with manufacturing in the fashion and textiles industry. Many investigations have demonstrated that the ant colony optimization (ACO) algorithm is effective and efficient for solving scheduling problems. This work applies a novel effective ant colony optimization (EACO) algorithm to solve two-stage flexible flow shop scheduling problems and thereby minimize earliness, tardiness, and makespan. Computational results reveal that for both small and large problems, EACO is more effective and robust than both the particle swarm optimization (PSO) algorithm and the ACO algorithm. Importantly, this work demonstrates that EACO can solve complex scheduling problems in an acceptable period of time.

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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