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Solving the Problems for Optimum Thickness of Protective Clothing in a Way of Improvement Based Particle Swarm Optimization

Abstract— This paper is the answer thesis to the questions of the Chinese University Students’ Mathematical Modeling Contest (A) in 2018. For the temperature distribution of high-temperature protective clothing, a one-dimensional thermal-conduction equation model established to obtain the numerical solution. And, a multi-objective optimization model is set up for various thicknesses of protective clothing in ideal evaluation method and the approximate optimal solution is obtained in collaborative optimization algorithm of multiple cities. Compared to the classic algorithm, the independently developed algorithm features stronger resistance to local convergence and is easier to obtain a better solution. For Question 1, the numerical solution is obtained for the one-dimensional thermal-conduction equation in Crank-Nicolson scheme and the temperature distribution of protective clothing is attained. The numerical solution is calculated and obtained for this equation in finite difference method and Crank-Nicolson scheme. About Question 2, based on Question 1, an ideal evaluation method based multi-objective optimization model is set up to obtain the optimum thickness of the Layer II of protective clothing. This paper considers the constrained conditions given in the title as optimization objectives and converts the multi-objective optimization model into single-objective optimization model in ideal evaluation method. As to Question 3, based on Question 2, this paper finds the solution for the multi-objective optimization problem in collaborative optimization algorithm of multiple cities. Application of this algorithm avoids enormous time consumption caused by traverse strategy. And, the sequent analysis gives an example analyzing the independently developed algorithm better than the other swarm smart algorithms against local convergence. This paper is advantageously characterized to obtain the numerical solution of a one-dimensional thermalconduction equation in a more accurate finite difference scheme and solves the multi-objective optimization problem in swarm smart algorithm. Compared to the classic algorithm, the independently developed algorithm features stronger resistance to local convergence and is easier to obtain a better solution.

Index Terms— One-dimensional thermal-conduction equation, Crank-Nicolson scheme, ideal evaluation method, and collaborative optimization algorithm of multiple cities

JinYang Zhang, LiuYang Xu, JiaQi Yang
Wuhan University of Technology, CHINA

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Cite: JinYang Zhang, LiuYang Xu, JiaQi Yang, "Solving the Problems for Optimum Thickness of Protective Clothing in a Way of Improvement Based Particle Swarm Optimization," Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering, pp. 444-453, Hong Kong, 15-17 June, 2019.