An Application for Improved Bee Colony Algorithm on A Multi-Objective Real-World Optimization Problem
Abstract
This paper presents an application of improved bee
colony algorithm for multi-objective optimization (IBMO) on a
real-world optimization problem known as welded beam design.
IBMO is founded on the principle of single objective artificial bee
colony algorithm (ABC). It also combines the nondominated
sorting strategy of NSGAII and classical multi-objective
optimization procedures such as Pareto-Dominance, crowding
distance, external archive, and etc. Furthermore, IBMO has an
improvement method to accelerate the convergence by
considering the number of function evaluations. By using several
benchmark problems, the running consistency and robustness of
IBMO has been reported in a previous study of authors. In this
study, IBMO determines the parameters of welded beam
engineering problem which has several constraints and two
objectives: (1) minimum cost and (2) minimum end deflection.
The experimental results are compared with two algorithms. The
results clearly show that IBMO reaches the better results easily
and it is a capable tool to solve multi-objective real world
optimization problems
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