Titlebook: Bioinspired Optimization Methods and Their Applications; 10th International C Marjan Mernik,Tome Eftimov,Matej ?repin?ek Conference proceed

jettison

,Performance Analysis of?Selected Evolutionary Algorithms on?Different Benchmark Functions,s no single solver which ranks as the best for each benchmark function. It is even harder to choose a solver for a specific optimization problem considering the computational complexity of the solver and the problem.

dissent

,Slime Mould Algorithm: An Experimental Study of?Nature-Inspired Optimiser, nature-inspired methods. All the algorithms are applied to 22 real-world problems called CEC?2011. Achieved results illustrate the good performance of the newly proposed SMA variants, especially compared with the original SMA algorithm.

確定無(wú)疑

不給啤

,An Agent-Based Model to?Investigate Different Behaviours in?a?Crowd Simulation,e considered: collaborative, acting attentively and collaboratively, and defector who, on the other hand, acts individually and recklessly. Many experimental simulations on different complexity scenarios were performed and each outcome indicates how the presence of a percentage of defector agents he

GIBE

,Accelerating Evolutionary Neural Architecture Search for?Remaining Useful Life Prediction,these DNNs are usually determined empirically, usually with the goal of minimizing prediction error without considering the time needed for training. However, such a design process is time-consuming as it is essentially based on trial-and-error. Moreover, this process may be inappropriate in those i

sphincter

,ACOCaRS: Ant Colony Optimization Algorithm for?Traveling Car Renter Problem,stics are natural choices for designing a new practical algorithm. Considering that Ant Colony Optimization (ACO) is well suited for other routing type of problems - in this paper we propose ACOCaRS - an algorithm for solving CaRS based on ACO. The proposed algorithm was investigated experimentally

輕快走過(guò)

incontinence

,CSS–A Cheap-Surrogate-Based Selection Operator for?Multi-objective Optimization,lity. Many algorithms use ensembles of surrogate models to boost the performance. Generally, the surrogate-based model either works out the solution’s fitness by approximating the evaluation function or selects the solution by weighting the uncertainty degree of candidate solutions. This paper propo

使混合

,Empirical Similarity Measure for?Metaheuristics,quently, there is an interest in understanding the similarities between metaheuristics. Previous studies have done theoretical analyses based on components and search strategies, providing insights into the relationship between different algorithms. In this paper, we argue that it is also important

irradicable

,Evaluation of?Parallel Hierarchical Differential Evolution for?Min-Max Optimization Problems Using es or disturbances in the input data may reduce the quality of the solution. One way to find a robust solution and consider uncertainty is to formulate the problem as a min-max optimization problem. Min-max optimization aims to identify solutions which remain feasible and of good quality under even