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Keywords = aerospace shell production scheduling problem

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15 pages, 3010 KB  
Article
An Improved Multi-Objective Evolutionary Approach for Aerospace Shell Production Scheduling Problem
by Qing Wang, Xiaoshuang Wang, Haiwei Luo and Jian Xiong
Symmetry 2020, 12(4), 509; https://doi.org/10.3390/sym12040509 - 1 Apr 2020
Cited by 8 | Viewed by 2970
Abstract
To certain degree, multi-objective optimization problems obey the law of symmetry, for instance, the minimum of one objective function corresponds to the maximum of another objective. To provide effective support for the multi-objective operation of the aerospace product shell production line, this paper [...] Read more.
To certain degree, multi-objective optimization problems obey the law of symmetry, for instance, the minimum of one objective function corresponds to the maximum of another objective. To provide effective support for the multi-objective operation of the aerospace product shell production line, this paper studies multi-objective aerospace shell production scheduling problems. Firstly, a multi-objective optimization model for the production scheduling of aerospace product shell production lines is established. In the presented model, the maximum completion time and the cost of production line construction are optimized simultaneously. Secondly, to tackle the characteristics of discreteness, non-convexity and strong NP difficulty of the multi-objective problem, a knowledge-driven multi-objective evolutionary algorithm is designed to solve the problem. In the proposed approach, structural features of the scheduling plan are extracted during the optimization process and used to guide the subsequent optimization process. Finally, a set of test instances is generated to illustrate the addressed problem and test the proposed approach. The experimental results show that the knowledge-driven multi-objective evolutionary algorithm designed in this paper has better performance than the two classic multi-objective optimization methods. Full article
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13 pages, 1196 KB  
Article
Evolutionary Algorithm for Aerospace Shell Product Digital Production Line Scheduling Problem
by Qing Wang, Haiwei Luo, Jian Xiong, Yanjie Song and Zhongshan Zhang
Symmetry 2019, 11(7), 849; https://doi.org/10.3390/sym11070849 - 1 Jul 2019
Cited by 11 | Viewed by 2737
Abstract
The production of aerospace shell products is directly related to the safety and reliability of aerospace products. In this work, the aerospace shell product digital production line scheduling problem (ASPDPLSP) was studied, and a solution was developed. In the production process, it is [...] Read more.
The production of aerospace shell products is directly related to the safety and reliability of aerospace products. In this work, the aerospace shell product digital production line scheduling problem (ASPDPLSP) was studied, and a solution was developed. In the production process, it is necessary to decide the processing machine and time of each operation. In order to create a scientific shell product production plan, we propose an operation scheduling algorithm (OSA). Based on the constraints of the inspection process, the OSA has two heuristic task scheduling rules. Then, in order to further optimize the product production plan, an improved genetic algorithm (IGA) is proposed. Considering the repeatability caused by random search, a method for the initial population generation with similar and diverse characteristics is proposed. Two of these generation rules retain symmetry and randomness. IGA was used to optimize the order in which the products were processed, resulting in lower costs. Simulation experiments showed that the proposed algorithm solved ASPDPLSP well and provided suggestions to produce aerospace shell products. Full article
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