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Evolutionary Algorithm for Aerospace Shell Product Digital Production Line Scheduling Problem

1
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
2
Capital Aerospace Machinery Corporation Limited, Beijing 100044, China
3
School of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, China
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(7), 849; https://doi.org/10.3390/sym11070849
Received: 4 June 2019 / Revised: 23 June 2019 / Accepted: 25 June 2019 / Published: 1 July 2019
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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 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. View Full-Text
Keywords: aerospace product; digital production line; evolutionary algorithm; genetic; scheduling aerospace product; digital production line; evolutionary algorithm; genetic; scheduling
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Wang, Q.; Luo, H.; Xiong, J.; Song, Y.; Zhang, Z. Evolutionary Algorithm for Aerospace Shell Product Digital Production Line Scheduling Problem. Symmetry 2019, 11, 849.

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