Mohammed Aljuaid
Papers
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Total Citations
1
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About
Mohammed Aljuaid is a rising researcher in the fields of evolutionary computation, human-robot collaboration, and fuzzy systems modeling. His most notable contribution is the development of a multi-objective bi-population evolutionary algorithm for human-robot collaborative disassembly sequence planning, which integrates interval type-2 fuzzy modeling to handle uncertainty in complex manufacturing environments. This work, published in 2025, has already garnered early citations, signaling its potential impact on sustainable production and intelligent automation. Aljuaid’s research addresses critical challenges in optimizing disassembly processes—key to recycling and remanufacturing—by balancing multiple objectives such as time, cost, and safety. His innovative use of bi-population strategies enhances algorithmic efficiency, while the incorporation of advanced fuzzy logic improves decision-making under ambiguity. Though early in his career, Aljuaid’s work bridges theoretical optimization with practical industrial applications, offering solutions for greener, more adaptive manufacturing systems. His contributions are particularly relevant for researchers and engineers seeking to advance collaborative robotics and sustainable production.
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