Incorporating of grey wolf optimization to the bees algorithm for continuous optimization in welded-beam design problem

Lim, Chin Xian (2018) Incorporating of grey wolf optimization to the bees algorithm for continuous optimization in welded-beam design problem. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

	Text (24 Pages) Incorporating Of Grey Wolf Optimization To The Bees Algorithm For Continuous Optimization In Welded-Beam Design Problem.pdf - Submitted Version Download (1MB)
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Abstract

In fact, there is no existing algorithm which is able to outperform the others on all optimization problems. Therefore, the continuous development of previous algorithms is important because the effectiveness of an algorithm in solving a set of problems will not guarantee its success in different kinds of test problems. However, the goal of this project is subjected as the incorporating of Grey Wolf Optimization (GWO) to the Bees Algorithm (BA) as the proposed algorithm in order to solve the continuous optimization in welded-beam design problem. The objectives of this project will covered the modified algorithm GWO-BA and showed the improvement of convergence speed of proposed algorithm towards searching of optimal solution against the previous BA. Thus, the benchmark test functions with several diverse properties will be the methods that to comparing the proposed algorithm and previous algorithms in order to analyze and validate the performance of the proposed algorithm. Based on the result of running test and simulation in the MATLAB software, the improvements of convergence speed and performance for modified GWO-BA against the standard BA were 48.12% based on the mean evaluation of 10 benchmark test functions and 37.43% based on the mean cost of welded-beam design problem.

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