UJ’s Prof Tartibu illuminated the path to transforming engineering optimisation

In today’s fast-paced technological landscape, solving intricate engineering problems has become a significant challenge. Conventional optimisation methods often struggle to find efficient solutions because of the complex and multifaceted nature of these issues. Lagouge Tartibu, a Professor in the field of Mechanical Engineering at the University of Johannesburg (UJ), believes there’s a game-changing solution to this problem.

From left to right: Prof Daniel Mashao, Executive Dean: Faculty of Engineering & the Built Environment; Prof Lagouge Tartibu; Dr Mpoti Ralephata. Chief Operating Officer

Prof Tartibu delivered his professorial inaugural address, titled “Evolutionary Algorithms: The Key to Cutting-Edge Engineering Optimisation,” at the University’s Ubuntu Chambers, Madibeng Building, Auckland Park Kingsway Campus on Monday, November 6, 2023. In his address, he delved into the exciting world of metaheuristic approaches, presenting them as a promising alternative for tackling complex engineering optimisation challenges.

Metaheuristic algorithms, he explained, draw inspiration from natural phenomena and problem-solving heuristics. They’ve demonstrated their effectiveness in navigating intricate solution spaces. By exploring the core principles of metaheuristics, including well-known algorithms like the ant colony optimisation algorithm, bat optimisation algorithm, whale optimisation algorithm, and grey wolf optimisation algorithm, Prof Tartibu shed light on how these versatile approaches can be tailored to formulate and address engineering problems effectively.

What’s most striking about these approaches is their adaptability and versatility. They’re not limited to a specific domain; instead, they’re well-suited for a wide range of applications. Whether you need to identify the shortest path, optimise mathematical equations, enhance machining performance, or fine-tune thermal systems, metaheuristics can offer valuable solutions, he explained.

During his presentation, Prof Tartibu consolidated his knowledge by showcasing tangible case studies and real-world applications. He emphasised the intricacies involved in defining engineering challenges, the effectiveness of machine learning models in forecasting and evaluating performance metrics, and the application of metaheuristic approaches to tackle multi-objective problems and derive optimal solutions.

In summary, he underlined the extraordinary potential of metaheuristics to bring about a revolution in the optimisation of intricate engineering problems, ushering in an era of innovative and sustainable solutions in the constantly evolving field of engineering.

Following Prof Tartibu’s address, Professor Tien-Chien Jen, Head of the Department of Mechanical Engineering Science at UJ, provided a brief response.

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