Cuckoo Search Algorithm with Lévy Flights for Global-Support Parametric Surface Approximation in Reverse Engineering

This paper concerns several important topics of the Symmetry journal, namely, computer-aided design, computational geometry, computer graphics, visualization, and pattern recognition. We also take advantage of the symmetric structure of the tensor-product surfaces, where the parametric variables u and v play a symmetric role in shape reconstruction. In this paper we address the general problem of global-support parametric surface approximation from clouds of data points for reverse engineering applications. Given a set of measured data points, the approximation is formulated as a nonlinear continuous least-squares optimization problem. Then, a recent metaheuristics called Cuckoo Search Algorithm (CSA) is applied to compute all relevant free variables of this minimization problem (namely, the data parameters and the surface poles). The method includes the iterative generation of new solutions by using the Lévy flights to promote the diversity of solutions and prevent stagnation. A critical advantage of this method is its simplicity: the CSA requires only two parameters, many fewer than any other metaheuristic approach, so the parameter tuning becomes a very easy task. The method is also simple to understand and easy to implement. Our approach has been applied to a benchmark of three illustrative sets of noisy data points corresponding to surfaces exhibiting several challenging features. Our experimental results show that the method performs very well even for the cases of noisy and unorganized data points. Therefore, the method can be directly used for real-world applications for reverse engineering without further pre/post-processing. Comparative work with the most classical mathematical techniques for this problem as well as a recent modification of the CSA called Improved CSA (ICSA) is also reported. Two nonparametric statistical tests show that our method outperforms the classical mathematical techniques and provides equivalent results to ICSA for all instances in our benchmark.This research work has received funding from the project PDE-GIR (Partial Differential Equations for Geometric modelling, Image processing, and shape Reconstruction) of the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant agreement No. 778035, the Spanish Ministry of Economy and Competitiveness (Computer Science National Program) under Grant #TIN2017-89275-R of the Agencia Estatal de Investigación and European Funds FEDER (AEI/FEDER, UE), and the project #JU12, jointly supported by public body SODERCAN of the Regional Government of Cantabria and European Funds FEDER (SODERCAN/FEDER UE). We also thank Toho University, Nihon University, and the Symmetry 2018, 10, 58 23 of 25 University of Cantabria for their support to conduct this research wor

A simple and effective geometric representation for irregular porous structure modeling

Computer-aided design of porous structures is a challenging task because of the high degree of irregularity and intricacy associated with the geometries. Most of the existing design approaches either target designing artifacts with regular-shaped pores or reconstructing geometric models from existing porous objects. For regular porous structures, it is difficult to control the pore shapes and distributions locally; for reconstructed models, a design is attainable only if there are some existing objects to reconstruct from. This paper is motivated to present an alternative approach to design irregular porous artifacts with controllable pore shapes and distributions, yet without requiring any existing objects as prerequisites. Inspired by the random colloid-aggregation model which explains the formation mechanism of random porous media, Voronoi tessellation is first generated to partition the space into a collection of compartments. Selective compartments are then merged together to imitate the random colloid aggregations. Through this Voronoi cell merging, irregular convex and concave polygons are obtained and the vertices of which are modeled as control points of closed B-Spline curves. The fitted B-Spline curves are then employed to represent the boundaries of the irregular-shaped pores. The proposed approach drastically improved the ease of irregular porous structure modeling while at the same time properly maintained the irregularity that is widely found in natural objects. Compared with other existing CAD approaches, the proposed approach can easily construct irregular porous structures which appear more natural and realistic. © 2010 Elsevier Ltd. All rights reserved.postprin

A Hybrid Bacterial Swarming Methodology for Job Shop Scheduling Environment

Optimized utilization of resources is the need of the hour in any manufacturing system. A properly planned schedule is often required to facilitate optimization. This makes scheduling a significant phase in any manufacturing scenario. The Job Shop Scheduling Problem is an operation sequencing problem on multiple machines with some operation and machine precedence constraints, aimed to find the best sequence of operations on each machine in order to optimize a set of objectives. Bacterial Foraging algorithm is a relatively new biologically inspired optimization technique proposed based on the foraging behaviour of E.coli bacteria. Harmony Search is a phenomenon mimicking algorithm devised by the improvisation process of musicians. In this research paper, Harmony Search is hybridized with bacterial foraging to improve its scheduling strategies. A proposed Harmony Bacterial Swarming Algorithm is developed and tested with benchmark Job Shop instances. Computational results have clearly shown the competence of our method in obtaining the best schedule