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The work describes a hybrid algorithm for the dynamic formation of a robot’s movement route in nondeterministic environments with bypassing stationary and nonstationary obstacles for two-dimensional space, based on the integration of wave and ant ...

The Particle Swarm Optimization (PSO) algorithm is a well-known and widely used technique for solving complex optimization problems, often providing very good results. However, precise parameter selection or auto-adaptation mechanisms are crucial for ...

This document describes how to extend the Internet Key Exchange Protocol Version 2 (IKEv2) to allow multiple key exchanges to take place while computing a shared secret during a Security Association (SA) setup.

This document utilizes the IKE_INTERMEDIATE ...

This paper proposes a hybrid algorithm combining STOA and DE, called STOA-ADE, for optimization problems. In STOA-ADE. Firstly, a mechanism of selecting mutation operators according to the diversity of the population is proposed to produce higher ...

Active Magnetic Regenerator (AMR) refrigeration is an innovate technology, which can reduce energy consumption and the depletion of the ozone layer. However, to develop a commercially applicable design of the AMR model is still an issue, because of the ...

Differential Evolution Strategy (DES) is a method that combines the differential mutation with the search direction adaptation mechanisms used by the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). Although earlier research on that algorithm ...

Integrating machine learning (ML) techniques into metaheuristics is an efficient approach in single-objective optimization. Indeed, high-quality solutions often contain relevant knowledge, that can be used to guide the heuristic towards promising areas. ...

Cloud computing represents relatively new paradigm of utilizing remote computing resources and is becoming increasingly important and popular technology, that supports on-demand (as needed) resource provisioning and releasing in almost real-time. Task ...

Genetic Algorithms (GA) explore the search space of an objective function via mutation and recombination. Crucial for the search dynamics is the maintenance of diversity in the population.

Inspired by tabu search we add a mechanism to an elitist GA's ...

Traveling Salesman Problem (TSP) is an intricate discrete hybrid optimization problem that is categorized as an NP‐Hard problem. The objective of the TSP is to find the shortest Hamilton route between cities to visit all existing cities and ...

In swarm intelligence, Particle Swarm Optimization (PSO) and Differential Evolution (DE) have been successfully applied in many optimization tasks, and a large number of variants, where novel algorithm operators or components are implemented, has been ...

The growing awareness of the environmental movement greatly influences the transportation scene of this century leading to several transportation alternatives. One among them is carsharing service which has been gaining traction and support in major ...

In this paper, we introduce staggered discontinuous Galerkin methods for the stationary Stokes flow on polygonal meshes. The proposed method is based on the pseudostress-velocity formulation. A Lagrange multiplier on dual edges is introduced to impose the ...

We propose a framework that allows us to analyze different variants of hybridizable discontinuous Galerkin (HDG) methods for the static Maxwell equations using one simple analysis. It reduces all the work to the construction of projections that best fit ...

Phylogenetic (hybridization) networks allow investigation of evolutionary species histories that involve complex phylogenetic events other than speciation, such as reassortment in virus evolution or introgressive hybridization in invertebrates and ...

Combinatorial optimization problems have several industrial applications such as Network routing, IOT network routing, path Planning for robotics and manufacturing for which the travelling Salesman Problem, TSP, can serve as typical test bench. ...

We propose a unified algebraic approach for the practical application and preconditioning of static condensation and hybridization, two popular techniques in finite element discretizations. We demonstrate the use of this algebraic framework for the ...

The aim of this work is to improve the results of the SVM classification (Support Vector Machine) by hybridizing the SVM classifier with the random forest classifier (Random Forest, RF) used as the auxiliary. Specification of the classification ...

The multi-point dynamic aggregation (MPDA) is a typical task planning problem. In order to solve the MPDA problem efficiently a hybrid differential evolution (DE) and estimation of distribution algorithm (EDA) called DE-EDA is proposed in this paper, ...

Differential evolution (DE) is a versatile and fast evolutionary algorithm (EA) for real world global optimization problems. It has been widely applied to diverse areas as a remarkable search technique. However, because of large step sizes in mutation, DE ...