SUMMARY
This paper presents an application of improved beecolony algorithm for multi-objective optimization (IBMO) on areal-world optimization problem known as welded beam design.IBMO is founded on the principle of single objective artificial beecolony algorithm (ABC). It also combines the nondominatedsorting strategy of NSGAII and classical multi-objectiveoptimization procedures such as Pareto-Dominance, crowdingdistance, external archive, and etc. Furthermore, IBMO has animprovement method to accelerate the convergence byconsidering the number of function evaluations. By using severalbenchmark problems, the running consistency and robustness ofIBMO has been reported in a previous study of authors. In thisstudy, IBMO determines the parameters of welded beamengineering problem which has several constraints and twoobjectives: (1) minimum cost and (2) minimum end deflection.The experimental results are compared with two algorithms. Theresults clearly show that IBMO reaches the better results easilyand it is a capable tool to solve multi-objective real worldoptimization problems