In this paper, we present a new algorithm — an Enhanced Annealing Genetic Algorithm for Multi-Objective Optimization problems (MOPs). The algorithm tackles the MOPs by a new quantitative measurement of the Pareto front coverage quality — Coverage Quotient. We then correspondingly design an energy function, a fitness function and a hybridization framework, and manage to achieve both satisfactory...

In the past decade, multi-UAV systems have gained significant attention and companies from in various fields. The main aims of growing such are able to operate a coordinated way complicated situations. To encompass increase speed applications, this research proposed optimization with intelligence. existing work, it does not detect collision effectively. Particle Swarm Optimization algorithm bas...

The article suggests an algorithm for regular classifier ensemble methodology. The proposed methodology is based on possibilistic aggregation to classify samples. The argued method optimizes an objective function that combines environment recognition, multi-criteria aggregation term and a learning term. The optimization aims at learning backgrounds as solid clusters in subspaces of the high...

Noisy optimization is currently receiving increasing popularity for its widespread applications in engineering optimization problems, where the objective functions are often found to be contaminated with noisy sensory measurements. In absence of knowledge of the noise-statistics, discriminating better trial solutions from the rest becomes difficult in the “selection” step of an evolutionary opt...

The goal of higher order mutation testing is to improve mutation testing effectiveness in particular and test effectiveness in general. There are different approaches which have been proposed in the area of second order mutation testing and higher order mutation testing with mutants order ranging from 2 to 70. Unfortunately, the empirical evidence on the relationship between the order of mutati...

Fitness landscapes are central in analyzing evolution, in particular for drug resistance mutations for bacteria and virus. We show that the fitness landscapes associated with antibiotic resistance are not compatible with any of the classical models; additive, uncorrelated and block fitness landscapes. The NK model is also discussed. It is frequently stated that virtually nothing is known about ...

While Interactive Evolutionary Computation (IEC) is starting to penetrate a larger scientific community, only few researchers have applied IEC to the design of complicated artifacts like machines or transportation systems. The present paper introduces a specific approach to Interactive Evolutionary Computation that breaches the two historical categories of user-defined fitness and selection in ...