Nature-inspiredmetaheuristic algorithms have become powerful and popular in computational intelligence and many applications. There are some important developments in recent years, and this special issue aims to provide a timely review of such developments, including ant colony optimization, bat algorithm, cuckoo search, particle swarm optimization, genetic algorithms, support vector machine, n...

Natural selection penalizes individuals that provide costly parental care to non-relatives. However, feedings to brood-parasitic fledglings by individuals other than their foster parents, although anecdotic, have been commonly observed, also in the great spotted cuckoo (Clamator glandarius)--magpie (Pica pica) system, but this behaviour has never been studied in depth. In a first experiment, we...

This paper proposes a novel hybrid t-way test generation strategy (where t indicates interaction strength), called High Level Hyper-Heuristic (HHH). HHH adopts Tabu Search as its high level meta-heuristic and leverages on the strength of four low level meta-heuristics, comprising of Teaching Learning based Optimization, Global Neighborhood Algorithm, Particle Swarm Optimization, and Cuckoo Sear...

One of the key stages in designing a heat exchanger is optimization process. The enhancement in thermal performance results in a rise in pressure drop and total annual costs. So, finding optimal dimensions of heat exchanger is a key stage in designing process. In this paper, optimization has been done based on entropy generation minimization, where Cuckoo Algorithm aided to reach better results...

The problem of data fitting is very important in many theoretical and applied fields. In this paper, we consider the problem of optimizing a weighted Bayesian energy functional for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to ...