Open Access

ARTICLE

Optimization of Aluminum Alloy Formation Process for Selective Laser Melting Using a Differential Evolution-Framed JAYA Algorithm

Siwen Xu¹, Hanning Chen², Rui Ni¹, Maowei He², Zhaodi Ge³, Xiaodan Liang^2,*

1 School of Mechanical Engineering, Tiangong University, Tianjin, 300387, China
2 School of Computer Science and Technology, Tiangong University, Tianjin, 300387, China
3 School of Control Science and Engineering, Tiangong University, Tianjin, 300387, China

* Corresponding Author: Xiaodan Liang. Email:

Computers, Materials & Continua 2026, 86(2), 1-25. https://doi.org/10.32604/cmc.2025.071398

Received 05 August 2025; Accepted 22 October 2025; Issue published 09 December 2025

Abstract

Selective Laser Melting (SLM), an advanced metal additive manufacturing technology, offers high precision and personalized customization advantages. However, selecting reasonable SLM parameters is challenging due to complex relationships. This study proposes a method for identifying the optimal process window by combining the simulation model with an optimization algorithm. JAYA is guided by the principle of preferential behavior towards best solutions and avoidance of worst ones, but it is prone to premature convergence thus leading to insufficient global search. To overcome limitations, this research proposes a Differential Evolution-framed JAYA algorithm (DEJAYA). DEJAYA incorporates four key enhancements to improve the flexibility of the original algorithm, which include DE framework design, horizontal crossover operator, longitudinal crossover operator, and global greedy strategy. The effectiveness of DEJAYA is rigorously evaluated by a suite of 23 distinct benchmark functions. Furthermore, the numerical simulation establishes AlSi10Mg single-track formation models, and DEJAYA successfully identified the optimal process window for this problem. Experimental results validate that DEJAYA effectively guides SLM parameter selection for AlSi10Mg.

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Keywords

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