Numerous clothing enterprises in the market have a relatively low efficiency of assembly line planning due to insufficient optimization of bottleneck stations.As a result,the production efficiency of the enterprise is...Numerous clothing enterprises in the market have a relatively low efficiency of assembly line planning due to insufficient optimization of bottleneck stations.As a result,the production efficiency of the enterprise is not high,and the production organization is not up to expectations.Aiming at the problem of flexible process route planning in garment workshops,a multi-object genetic algorithm is proposed to solve the assembly line bal-ance optimization problem and minimize the machine adjustment path.The encoding method adopts the object-oriented path representation method,and the initial population is generated by random topology sorting based on an in-degree selection mechanism.The multi-object genetic algorithm improves the mutation and crossover operations according to the characteristics of the clothing process to avoid the generation of invalid offspring.In the iterative process,the bottleneck station is optimized by reasonable process splitting,and process allocation conforms to the strict limit of the station on the number of machines in order to improve the compilation efficiency.The effectiveness and feasibility of the multi-object genetic algorithm are proven by the analysis of clothing cases.Compared with the artificial allocation process,the compilation efficiency of MOGA is increased by more than 15%and completes the optimization of the minimum machine adjustment path.The results are in line with the expected optimization effect.展开更多
This paper focuses on the scheduling problem in assembly islands environment with fixed-position layouts. In such configuration, the product normally remains in one location for its entire manufacturing period while m...This paper focuses on the scheduling problem in assembly islands environment with fixed-position layouts. In such configuration, the product normally remains in one location for its entire manufacturing period while machines, materials and workers are moved to an assembly site called an assembly island. This production layout has some unique features such as moving assembly workers, tools and materials; limited space at assembly site; considerable distance between islands. The authors first give the definition and mathematical model for the scheduling problem and then propose a two-level genetic algorithm to obtain a near optimal solution to minimize the makespan. Experimental results show that this algorithm is effective. The performance analysis of the proposed algorithm indicates that it is more efficient in the airline or shipbuilding industry than in the machine or tool final assembly companies.展开更多
A new way to solve the scheduling problem ofgarment assembly line based on genetic algorithmwas proposed. The chromosome was decoded usingtask precedence relation and after the operation ofreproduction, crossover and ...A new way to solve the scheduling problem ofgarment assembly line based on genetic algorithmwas proposed. The chromosome was decoded usingtask precedence relation and after the operation ofreproduction, crossover and mutation, the globaloptimal result can be obtained. Fitness function wasrepresented by smoothness Index ( SI ). Thesimulation shows that the method proposed in thispaper is better than the conventional way and theoptimized solution can be got in this way.展开更多
基金supported by Key R&D project of Zhejiang Province (2018C01005),http://kjt.zj.gov.cn/.
文摘Numerous clothing enterprises in the market have a relatively low efficiency of assembly line planning due to insufficient optimization of bottleneck stations.As a result,the production efficiency of the enterprise is not high,and the production organization is not up to expectations.Aiming at the problem of flexible process route planning in garment workshops,a multi-object genetic algorithm is proposed to solve the assembly line bal-ance optimization problem and minimize the machine adjustment path.The encoding method adopts the object-oriented path representation method,and the initial population is generated by random topology sorting based on an in-degree selection mechanism.The multi-object genetic algorithm improves the mutation and crossover operations according to the characteristics of the clothing process to avoid the generation of invalid offspring.In the iterative process,the bottleneck station is optimized by reasonable process splitting,and process allocation conforms to the strict limit of the station on the number of machines in order to improve the compilation efficiency.The effectiveness and feasibility of the multi-object genetic algorithm are proven by the analysis of clothing cases.Compared with the artificial allocation process,the compilation efficiency of MOGA is increased by more than 15%and completes the optimization of the minimum machine adjustment path.The results are in line with the expected optimization effect.
基金supported by HKSAR ITF (GHP/042/07LP),HKSAR RGC and from industrial collaborators
文摘This paper focuses on the scheduling problem in assembly islands environment with fixed-position layouts. In such configuration, the product normally remains in one location for its entire manufacturing period while machines, materials and workers are moved to an assembly site called an assembly island. This production layout has some unique features such as moving assembly workers, tools and materials; limited space at assembly site; considerable distance between islands. The authors first give the definition and mathematical model for the scheduling problem and then propose a two-level genetic algorithm to obtain a near optimal solution to minimize the makespan. Experimental results show that this algorithm is effective. The performance analysis of the proposed algorithm indicates that it is more efficient in the airline or shipbuilding industry than in the machine or tool final assembly companies.
基金Financed by Henan provincial Fund (No. 0324300201)
文摘A new way to solve the scheduling problem ofgarment assembly line based on genetic algorithmwas proposed. The chromosome was decoded usingtask precedence relation and after the operation ofreproduction, crossover and mutation, the globaloptimal result can be obtained. Fitness function wasrepresented by smoothness Index ( SI ). Thesimulation shows that the method proposed in thispaper is better than the conventional way and theoptimized solution can be got in this way.
