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| Research on Facility Layout of Unmanned Bookstore Based on an Improved Genetic Algorithm |
| DOU Shuihai1, JI Mengxin1, ZHU Huiqi2, DU Yanping1, WANG Zhaohua1, LI Wenjing3, SU Xianyang4
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1. Beijing Institute of Graphic Communication, a. School of Mechanical and Electrical Engineering; b. Comprehensive Laboratory of Key TechnologyApplication Research and Service in the Field of Press and Publishing, Beijing 102600, China;
2. School of Transportation, Ludong University, Yantai 264025, China;
3. School of Economics and Management, North China Electric Power University, Beijing 102206, China;
4. Beijing Huacheng Electronics Co, Ltd, Beijing 100176, China |
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Abstract In order to reduce unnecessary book handling and readers' waiting time, this paper takes the unmanned bookstore as the research object, sets the coordinates of the centre point of the operation area as the decision variables, and constructs an unmanned bookstore facility layout optimization model with the goal of the shortest book handling time and the largest comprehensive relationship of the operation area under the constraints of the safety distance of the operation unit, the relation between the operation area area and the overall area, and the limitation of the access gate passageway, etc, and uses the SLP method as the initial solution for the layout scheme. The layout scheme obtained is used as the initial solution of the genetic algorithm, and a simulated annealing algorithm Metropolis acceptance criterion is introduced in its cross-variation stage to propose an improved genetic algorithm for solving. After taking an unmanned bookstore as an example, comparing the optimal value of book handling time, the value of the integrated relationship between operation areas and the optimal value of the objective function of the layout scheme obtained by the genetic algorithm, SLP+genetic method, genetic simulated annealing algorithm, and improved genetic algorithm, the results show that the improved genetic algorithm is the most effective, and the layout of the facilities obtained by the scheme is more scientific and reasonable, which can effectively save the time of completing readers' orders, and enhance the customers' book buying and reading experience. The results show that the improved genetic algorithm is optimal and the proposed facility layout scheme is more scientific and reasonable.
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Received: 12 June 2024
Published: 14 July 2026
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