Clustering and Genetic Algorithm Based Hybrid Flowshop Scheduling with Multiple Operations

Yingfeng Zhang,Shudong Sun,Sichao Liu

doi:10.1155/2014/167073

Yingfeng Zhang, Shudong Sun + Show 1 more

Open Access

https://doi.org/10.1155/2014/167073

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Abstract

This research is motivated by a flowshop scheduling problem of our collaborative manufacturing company for aeronautic products. The heat-treatment stage (HTS) and precision forging stage (PFS) of the case are selected as a two-stage hybrid flowshop system. In HTS, there are four parallel machines and each machine can process a batch of jobs simultaneously. In PFS, there are two machines. Each machine can install any module of the four modules for processing the workpeices with different sizes. The problem is characterized by many constraints, such as batching operation, blocking environment, and setup time and working time limitations of modules, and so forth. In order to deal with the above special characteristics, the clustering and genetic algorithm is used to calculate the good solution for the two-stage hybrid flowshop problem. The clustering is used to group the jobs according to the processing ranges of the different modules of PFS. The genetic algorithm is used to schedule the optimal sequence of the grouped jobs for the HTS and PFS. Finally, a case study is used to demonstrate the efficiency and effectiveness of the designed genetic algorithm.

Highlights

This research is motivated by a flowshop scheduling problem of our collaborative manufacturing company for aeronautic product
The clustering is used to group the jobs according to the processing ranges of the different modules of precision forging stage (PFS)
There are many WIP blocked for PFS because the multiple workpieces with different sizes can be simultaneously processed in each machine of heat-treatment stage (HTS)

Summary

Introduction

This research is motivated by a flowshop scheduling problem of our collaborative manufacturing company for aeronautic product This company is composed of a set of multiple stages with each stage having parallel machines. There are many WIP blocked for PFS because the multiple workpieces with different sizes can be simultaneously processed in each machine of HTS. In contrast to general hybrid flowshop scheduling, some characteristics which emerged in this industrial case have substantiated the complexity of the problem. Each machine can install any module of the four modules for processing the workpieces with different sizes, and the setup time and working time of each module should be considered

Machine 2

Literature Review

Mathematical Model

Clustering and GA-Based Scheduling Method

Case Study

Conclusion