An Isolated Microgrid (IMG) is an electrical distribution network combined with modern information technologies aiming at reducing costs and pollution to the environment. In this article, we implement the Bacterial Foraging Optimization Algorithm (BFOA) to optimize an IMG model, which includes renewable energy sources, such as wind and solar, as well as a conventional generation unit based on diesel fuel. Two novel versions of the BFOA were implemented and tested: Two-Swim Modified BFOA (TS-MBFOA), and Normalized TS-MBFOA (NTS-MBFOA). In a first experiment, the TS-MBFOA parameters were calibrated through a set of 87 independent runs. In a second experiment, 30 independent runs of both TS-MBFOA and NTS-MBFOA were conducted to compare their performance on minimizing the IMG using the best parameter tuning. Results showed that TS-MBFOA obtained better numerical solutions compared to NTS-MBFOA and LSHADE-CV, an Evolutionary Algorithm, found in the literature. However, the best solution found by NTS-MBFOA is better from a mechatronic point of view because it favors the lifetime of the IMG, resulting in economic savings in the long term.

In this paper, a graph-theory-based approach for representing planar mechanisms is presented, the Santiago Portilla method (SPM). From the corresponding adjacency matrix, SPM generates an extended matrix containing the complete characterization of a planar mechanism, including all the information about both topology and geometry. This matrix representation can be used for the optimal design of mechanisms, allowing simultaneously the topological and dimensional synthesis by means of computational tools such as the metaheuristic algorithms. A case study corresponding to the design of a fixed-linear-trajectory tracker mechanism is included in order to test the efficiency of the proposed approach. It was carried out by addressing the design as an optimization problem and solving it with the differential evolution algorithm, representing the individuals in its population by the matrix form generated by the SPM. The results of the case study show that the SPM and its matrix representation constitute a useful and flexible tool for the solution of the real engineering problems involving the design of planar mechanisms.

In this work, a new version of the Harmony Search algorithm for solving multi-objective optimization problems is proposed, MOHSg, with pitch adjustment using genotype. The main contribution consists of adjusting the pitch using the crowding distance by genotype; that is, the distancing in the search space. This adjustment automatically regulates the exploration–exploitation balance of the algorithm, based on the distribution of the harmonies in the search space during the formation of Pareto fronts. Therefore, MOHSg only requires the presetting of the harmony memory accepting rate and pitch adjustment rate for its operation, avoiding the use of a static bandwidth or dynamic parameters. MOHSg was tested through the execution of diverse test functions, and it was able to produce results similar or better than those generated by algorithms that constitute search variants of harmonies, representative of the state-of-the-art in multi-objective optimization with HS.

There are problems that are difficult to solve through mathematical programming or by classical methods. These problems are called hard problems due to their high complexity or high dimension. On the other hand, mataheuristics intends to seek a better solution to a problem. The Improvement Harmony Search algorithm is proposed under modification of the bandwidth parameter increasing the quality of the exploitation of the solutions. That is why within the state of the art, are mentioned several versions of harmonic search. The state of the art is supports the fact that the algorithm belongs to the category of those who make modifications to its parameters. This research demonstrates the ability of ImHS to solve a problem of high complexity focused on solving four-bar mechanism designs, whose solutions imply high dimension and which are also classified as hard problems. The two problems that are solved in this investigation, are problems very attacked within the state of the art by various metaheuristics. A comparison is then made against previous solutions with traditional metaheuristics and other versions of harmony search algorithm. Finally, the effectiveness of performance is demonstrated, where proposed algorithm it exceeded five metaheuristic algorithms and five harmony search versions. An optimum is provided in an easy and useful way, the parametric statistics are improved and the number of feasible solutions is exceeded in NP-hard problems as in the case of problems with four-bar mechanisms.

In this paper, an alternative approach for topology optimization of truss-type structures is presented. The structural design is translated to a constrained discrete optimization problem based on weight reduction, with performance considerations included in its objective function. The constraints are related to the maximum global stress and to the individual strain energy density. Each member has a standard profile and its absence/presence in the structural representation is implemented with a binary coding; in order to avoid singularities while in the structural analysis, a scheme for simulating the effects of missing members by means of the birth/death element technique is applied. An energy-based approach is employed to detect those elements that not contribute to the overall stiffness. The optimization problem is solved by applying a Modified Binary Differential Evolution algorithm, and the graph theory is applied in parallel with the optimization process to discard unfeasible structures and reduce execution time. The structural performance is evaluated by an execution-time static analysis based on the finite-element method, considering the behavior in a 3-D environment and using commercial software to reduce the uncertainty in this step. The presented proposal is implemented in ANSYS APDL, using as case studies two different structures with a specific load case. The obtained results show a volume reduction of more than 40% off the initial structures, indicating that the proposed approach can be a high-quality tool for structural design in real engineering problems.

This paper presents a dynamic approach to the synthesis of a crank-rocker four-bar mechanism, that is obtained by an optimization problem and its solution using the Bio-inspired algorithm called Differential Evolution (DE). The proposed dynamic approach states a mono-objective dynamic optimization problem (MODOP), in order to obtain a set of optimal parameters of the system. In this MODOP, the kinematic and dynamic models of the whole system are considered as well as a set of constraints including a dynamic constraint. The DE algorithm is adapted to solve the optimization problem by adding a suitable constraint-handling mechanism that is able to incorporate the kinematic and dynamic constraints of the system. A set of independent computational runs were carried out in order to validate the dynamic approach. An analysis from the mechanical and computational point of view is presented, based on the obtained results. From the analysis of the simulation and its results, it is shown that the solutions for the proposed algorithm lead to a more suitable design based on the dynamic approach.