The present work aims at introducing a robust optimization algorithm called “CMAC-engine”, a blended scheme of Ant Colony Optimization (ACO) and Cost Minimization (CM) algorithms. The feasibility of CMAC-engine is numerically experimented by solving a standard 25-bar space truss in the field of structural engineering. The optimal design obtained using CMAC-engine is then compared with the global optimum designs obtained using other popular heuristics like Genetic Algorithm (GA), Tabu Search (TS), and Simulated Annealing (SA). Numerical investigation confirms that CMAC-engine is superior in terms of quality of the solution and functional evaluations over other optimization techniques in achieving world-class solution.
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Murugadoss et al. (2007) studied this question.
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