In order to reduce the memory footprint and energy consumption of embedded microcontroller in mobile robot, the concise differential evolution algorithm based on chaotic local search (CDE-CLS) is proposed for online optimization of recurrent fuzzy neural network (RFNN) controller in robot path planning so that the robot can be adaptive real-time obstacle avoidance. The CDE-CLS algorithm reduces...

Diversity of the population in a genetic algorithm plays an important role in impeding premature convergence. This paper proposes an adaptive neurofuzzy inference system genetic algorithm based on sexual selection. In this technique, for choosing the female chromosome during sexual selection, a bilinear allocation lifetime approach is used to label the chromosomes based on their fitness value w...

This paper presents a novel modified particle swarm optimization algorithm (MPSO) for both offline and online parametric identification of dynamic models. The MPSO is applied for identifying a suspension system introduced by a quarter-car model. A novel mutation mechanism is employed in MPSO to enhance global search ability and increase convergence speed of basic PSO (BPSO) algorithm. MPSO opti...

The evolution of computing technology and the ever increasing size and variety of data sets have created a new range of problems and challenges for data analysts, as well as new opportunities for intelligent systems in data analysis. This study concentrates on performing experimental analysis to find regression base outlier and influential point using two standard algorithms for data clustering...

The Bacterial Evolutionary Algorithm (BEA) is a relatively new type of evolutionary algorithm and shows the typical phenomena of stochastic optimization methods. Two of these phenomena: premature convergence and low convergence speed near the optimum are often in connection with the low genetic diversity of the population. Variation of genetic diversity in the original BEA and in its three para...

The open vehicle routing problem (OVRP) is a variance of the vehicle routing problem (VRP) that has a unique character which is its open path form. This means that the vehicles are not required to return to the depot after completing service. Because this problem belongs to the NP-hard problems, many metaheuristic approaches like the ant colony optimization (ACO) have been used to solve OVRP in...

premature ovarian failure (pof) is a heterogeneous syndrome with several causative factors. autoimmune mechanisms are involved in pathogenesis of 4-30 % of pof cases. the present review focuses on the role of autoimmunity in the pathophysiology of pof. the evidences for an autoimmune etiology are: demonstration of ovarian autoantibodies, the presence of lymphocytic oophoritis, and association w...

For effective optimization, metaheuristics should maintain the proper balance between exploration and exploitation. However, standard firefly algorithm (FA) posted some limitations in its process that can eventually lead to premature convergence, affecting performance adding uncertainty optimization results. To address these constraints, this study introduces an additional novel search mechanis...

Brain-storm optimization (BSO), which is a population-based algorithm, exhibits poor search performance, premature convergence, and high probability of falling into local optima. To address these problems, we developed the adaptive mechanism-based BSO (ABSO) algorithm based on chaotic in this study. The adjustment space using method an self-scaling mechanism balances global development performa...

The traveling salesman problem (TSP) is one of the most important combinational optimization problems that have nowadays received much attention because of its practical applications in industrial and service problems. In this paper, a hybrid two-phase meta-heuristic algorithm called MACSGA used for solving the TSP is presented. At the first stage, the TSP is solved by the modified ant colony s...