Ant colony optimization is a well established metaheuristic from the swarm intelligence field
for solving difficult optimization problems. In this work we present an application of ant …

Cities are constantly transforming and, consequently, attracting efforts from researchers and
opportunities to the industry. New transportation systems are being built in order to meet …

Abstract This work proposes Adaptive Facilitated Mutation, a self-adaptive mutation method
for Structured Grammatical Evolution (SGE), biologically inspired by the theory of facilitated …

Optimization tasks are often complex, CPU-time consuming and usually deal with finding the
best (or good enough) solution among alternatives for a given problem. Parallel …

Background The function of a protein is determined by its native protein structure. Among
many protein prediction methods, the Hydrophobic-Polar (HP) model, an ab initio method …

Here we propose an evolutionary algorithm that self modifies its operators at the same time
that candidate solutions are evolved. This tackles convergence and lack of diversity issues …

Cover scheduling problem in wireless sensor networks (WSN-CSP) aims to find a schedule
of covers which minimizes the longest continuous duration of time for which no sensor in the …

This paper deals with an NP-hard problem called the colored balanced traveling salesman
problem (CBTSP), which is a variation of colored traveling salesman problem (CTSP) which …

This paper presents a two-membered evolution strategy based approach to address the total
rotation minimization problem (TRMP) pertaining to directional sensor networks. TRMP is an …

Evolutionary Algorithms (EA) different EA flavors are due to different variation and selection
methods: classical Evolution Strategies (ES) typically use truncation selection in contrast to …