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In this paper, Subpopulation Firefly Algorithm is proposed for optimization of machining parameters in multi-pass turning and multi-pass face milling operations. Basic Firefly Algorithm is modified with the aim to avoid space of local minimum and to meet the operation constraints in each iteration step. For that purpose, the following modifications are made: one firefly population is divided into two, a crossover operator is introduced and the searching for new design variables is continued until constraint functions are fulfilled. For turning operation, optimization is carried out for one objective: minimization of production cost. For face milling operation, multi-objective optimization is used for minimizing production cost and machining time, and maximizing profit rate at the same time. In both cases of multi-pass machining operations, optimization process implies meeting all operation constraints. For multi-pass turning operation, the best results from literature are confirmed with good convergence and low value of standard deviation. For multi-pass milling operation, better results are achieved compared with existing results from literature. The proposed algorithm showed capability of achieving global optimum for complex optimization problems.

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The standard Bat algorithm (BA) is extended by introducing a bat family for the purpose of continuous repetition of the procedure for searching for an optimal solution. The standard BA is modified by including the loop search in the zone of solutions. For each bat, in each family, fine search according to the step of Lévy-flight is used for looking for an improved solution until the given constraints are satisfied. Such solutions are compared for each bat family and the best one is selected. The loop bat family algorithm (Loop BFA) is tested on five engineering examples known in the literature. The correctness and efficiency of the proposed algorithm are verified by good results in these examples.

This paper presents a comparative analysis of the application of biologically inspired algorithms and methodologies in CAD software packages, for determining the optimal profile values in carriers with two independent variables. As an example of a biologically inspired algorithm to solve this optimization problem, the scroll algorithm was applied, while the SolidWorks software package was used as an example of CAD.