Comparison of classical and heuristic methods for solving engineering design problems

Abstract

This paper presents an innovative application of the Ant Colony Optimization (ACO) algorithm to optimize engineering problems, specifically on welded beams and pressure vessels. A simulation study was conducted to evaluate the performance of the new ACO algorithm, comparing it with classical optimization techniques and other heuristic algorithms previously discussed in the literature. The algorithm was executed 20 times to obtain the most efficient results. The best performance outcome in the welded beam simulation was 1.7288, achieved after 540 iterations using 1000 ants, with a computation time of 6.27 seconds. Similarly, the best performance result in the pressure vessel simulation was 5947.1735, obtained after 735 iterations using 1000 ants and completed in 6.97 seconds. Compared to similar results reported in the literature, the new ACO algorithm demonstrated superior performance, offering an outstanding solution. Additionally, users can utilize this new ACO algorithm to quickly acquire information about welded beam design and prefabrication through simulation.

Keywords

• ant colony
• engineering design
• MATLAB
• optimization
• welded beam design
• pressure vessel

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