Electromagnetism-like algorithm (EM) is a population-based metaheuristic which has been proposed to solve continuous problems effectively. In this paper, we present a new meta-heuristic that uses the EM methodology to solve the single machine scheduling problem. Single machine scheduling is a combinatorial optimization problem. Schedule representation for our problem is based on random keys. Be...

An online map building evolutionary algorithm is proposed using multi-agent mobile robots with odometric uncertainty. The control algorithm for map building in each robot is identical and trained by online evolutionary algorithm (EA). Each robot has configuration uncertainty which increases as it moves, and it perceives the surrounding environment information by the limited range sensors. It co...

In this paper, we investigate the convergence of a novel simulation scheme to the target diffusion process. This scheme, the Quasi-EA, is closely related to the Exact Algorithm (EA) for diffusion processes, as it is obtained by neglecting the rejection step in EA. We prove the existence of a myopic coupling between the QuasiEA and the diffusion. Moreover, an upper bound for the coupling probabi...

In this paper, a novel method for tuning the design of an evolutionary algorithm (EA) is presented. The ADT method was built from a practical point of view, for including an EA into a framework for optimizing machining processes under uncertainties. The optimization problem studied, the algorithm, and the computer experiments made using the ADT method are presented with many details, in order t...

We propose the Clustering Based Niching (CBN) method for Evolutionary Algorithms (EA) to identify multiple global and local optima in a multimodal search space. The basic idea is to apply the biological concept of species in separate ecological niches to EA to preserve diversity. We model species using a multipopulation approach, one population for each species. To identify species in a EA popu...

Vertex cover is one of the best known NP-Hard combinatorial optimization problems. Experimental work has claimed that evolutionary algorithms (EAs) perform fairly well for the problem and can compete with problem-specific ones. A theoretical analysis that explains these empirical results is presented concerning the random local search algorithm and the (1 + 1)-EA. Since it is not expected that ...

The matrix exponential is a much-studied matrix function having many applications. The Fréchet derivative of the matrix exponential describes the first-order sensitivity of eA to perturbations in A and its norm determines a condition number for eA. Among the numerous methods for computing eA the scaling and squaring method is the most widely used. We show that the implementation of the method i...

The problem of obtaining a discrete curve approximation to data points appears recurrently in several real-world fields, such as CAD/CAM (construction of car bodies, ship hulls, airplane fuselage), computer graphics and animation, medicine, and many others. Although polynomial blending functions are usually applied to solve this problem, some shapes cannot yet be adequately approximated by usin...

We introduce a novel evolutionary algorithm where the centralized oracle –the selection-reproduction loop– is replaced by a distributed system of Fate Agents that autonomously perform the evolutionary operations. This results in a distributed, situated, and self-organizing EA, where candidate solutions and Fate Agents co-exist and co-evolve. Our motivation comes from evolutionary swarm robotics...