Ant Lion Optimizer-Based Multi-Objective Optimization of Laser Welding for Joining Ti6Al4V and AISI 316L

The Ti6Al4V/AISI 316L dissimilar welded joint has significant industrial applications because of its outstandingmechanical and corrosion resistance properties. However, welding dissimilar metals is difficult due to the inevitable generation of brittle intermetallic compounds, which degrade mechanical strength. Ensuring superior laser weld quality is essential for various industrial applications. This research explores how critical process variables—laser power, beam offset and welding speed—affect joint strength (ultimate) and microhardness. The study uses RSM (Response Surface Methodology) to establish predictive models linking the input parameters with weld quality. Despite its usefulness, conventional deterministic optimization methods within RSM are prone to getting trapped in local optima, which can prevent identification of the most effective parameter settings. To address this issue, a nature-inspired metaheuristic, the Ant Lion Optimizer-Based Multi-Objective Optimization (MOALO), is introduced for enhanced optimization performance. The optimization decisions are validated by analysing MOALO with MOPSO and NSGA-II. The findings indicate that with a welding speed of 1 mm/sec, a beam offset of 0.5 mm, and a laser power of 315.50 W, the optimized ultimate tensile strength reaches 101.73 MPa, while the average weld zone microhardness is 333.60 HV. The results show good agreement—and are slightly superior to those obtained using NSGA-II and MOPSO—confirming the effectiveness of MOALO in optimizing the laser welding process.