Application of adaptive bats sonar algorithm to minimise car side impact design

• Main Author: Tan, Hon Seong
• Format: Undergraduates Project Papers
• Language: English
• Published: 2017
• Subjects: TS Manufactures
• Online Access: http://umpir.ump.edu.my/id/eprint/26049/1/27.Application%20of%20adaptive%20bats%20sonar%20algorithm%20to%20minimise%20car%20side.pdf; http://umpir.ump.edu.my/id/eprint/26049/; https://efind.ump.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=7438

This project was focusing on the modification of bats sonar algorithm (BSA) and renamed to adaptive bats sonar algorithm (ABSA) due to some limitations of previous algorithm. ABSA was an improved version algorithm which include the real bats echolocation characteristics to search prey and reciprocal altruism mechanism as compared to original BSA. This project became a platform to show the superior performance of ABSA. Due to much time was needed to solve all the equations of car side impact design (CSID) if using the traditional way such as try and error method and wrong calculation may happened when solved them manually, it was necessary to implement ABSA to optimise the CSID application by minimise the total weight of car side. ABSA was developed by using computer simulation method in MA TLAB software. It was made in matrix form that initialise from selecting the random bats number between 700 and 1000 and stochastically placed them in the starting position and undergone searching process. The ABSA was performed in two benchmark functions with each 30 runs and after the results were satisfied with the given optimum results, it was performed in CSID with 100 runs to obtain the best minimum weight of car side. The best objective function was compared with the existing results of other swarm intelligence algorithms. The comparison showed the excellent performance of developed ABSA to solve single constrained optimisation problems.