Directed jaya algorithm for delivering nano-robots to cancer area.

Area of Science:

• Biomedical Engineering
• Nanotechnology
• Computational Intelligence

Background:

• Nanorobot drug delivery is a promising cancer treatment strategy.
• Efficient navigation and deployment of nanorobots are critical for therapeutic success.
• Existing algorithms like Jaya and Directed Particle Swarm Optimization (DPSO) have limitations in speed and efficiency.

Purpose of the Study:

• To compare the efficiency of Jaya and DPSO algorithms for nanorobot drug delivery.
• To propose a novel hybrid algorithm, Directed Jaya (DJaya), combining Jaya and DPSO.
• To introduce a new strategy for efficient cancer cell destruction using nanorobots.

Main Methods:

• Comparative analysis of Jaya and DPSO algorithms.
• Development and implementation of the Directed Jaya (DJaya) hybrid algorithm.
• Experimental validation of DJaya's performance against Jaya and DPSO.

Main Results:

• DJaya demonstrates higher efficiency in nanorobot delivery compared to Jaya and DPSO.
• DJaya initiates nanorobot delivery earlier than DPSO, facilitating prompt drug release.
• DJaya completes nanorobot delivery faster than Jaya, ensuring timely drug dosage.
• DJaya effectively groups nanorobots in the target area, similar to DPSO, optimizing drug release.
• The proposed cancer cell destruction strategy saves approximately 40% of nanorobots.

Conclusions:

• The DJaya algorithm offers a significant advancement in nanorobot-based cancer therapy.
• DJaya enhances drug delivery efficiency and speed, leading to potentially better treatment outcomes.
• The novel cancer cell destruction strategy optimizes nanorobot utilization and reduces waste.