scholarly journals A Study of Flexible Flow Shop Scheduling Problem with Various Heterogeneous Labors

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Rong-Hwa Huang ◽  
Shao-Jung Chang ◽  
Shun-Chi Yu
Keyword(s):  
Production Planning ◽  
Processing Time ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Deterioration Rate ◽  
Physical Deterioration ◽  
Average Improvement ◽  
The Disabled ◽  
And Control ◽  
Flexible Flow Shop Scheduling

This study considers the necessity of hiring heterogeneous labors. So far, many studies focus more on manufacturing of equipment and control systems in the intelligent production planning. In fact, the regular labors’ processing time may be affected by the external factors and the disabled labors by the mentally handicapped. Therefore, this study sets the processing time of the two types of labors as fuzzy sets. The extra processing time from overtime generated by physical deterioration of old-aged labors is equal to the processing time of regular labors multiplied by the physical deterioration rate of old-aged labors on machine. The coefficient of the cost function is the stepwise function of cost structure. Besides, the dispatching rule based on floating time utilizes ant colony optimization to minimize the makespan. The data test results indicate that the proposed algorithm can efficiently dispatch and schedule the operations, with the average improvement ratio about 11.76%, and demonstrates high capability for the intelligent production planning

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.

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.

The Research of Heuristic Algorithm for Flow Shop Scheduling Problem

2012 ◽  
Vol 605-607 ◽  
pp. 528-531
Author(s):  
Dan Tang ◽  
Hong Ping Shu
Keyword(s):  
Heuristic Algorithm ◽  
Processing Time ◽  
Flow Shop ◽  
Heuristic Method ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Average Quality ◽  
Simulation Experiments ◽  
Shop Scheduling ◽  
Better Than

For the flow shop scheduling problem which aims to minimize makespan, this paper gives a new derivation about its mathematical definition, and mining characteristics of the problem itself further. By which analysis, the new heuristic method proposed in the paper shorten the waiting time of each job as much as possible on the basis of reduce the processing time of the first machine and last job. The result of simulation experiments shows that, our new heuristic algorithm has good performance, and the average quality and stability of scheduling sequences generated by new method is significantly better than other heuristic algorithm which has the same complexity.

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