Genetic Algorithms are heuristic search approaches that are applicable to a wide range of
optimization problems. This flexibility makes them attractive for many optimization problems …

Agricultural production has become a key factor for the stability of the world economy. The
use of pesticides provides a more favorable environment for the crops in agricultural …

This paper proposes rain-fall optimization algorithm (RFO), a new nature-inspired algorithm
based on behavior of raindrops, for solving of real-valued numerical optimization problems …

Explaining to what extent the real power of genetic algorithms (GAs) lies in the ability of
crossover to recombine individuals into higher quality solutions is an important problem in …

Although creativity is encouraged in the abstract it is often discouraged in educational and
workplace settings. Using an agent-based model of cultural evolution, we investigated the …

We reinvestigate a fundamental question: How effective is crossover in genetic algorithms in
combining building blocks of good solutions? Although this has been discussed …

This paper is concerned with the solution procedure of a multi-objective fuzzy stochastic
optimisation problem by simulation-based genetic algorithm. In this article, a multi-objective …

A cellular automaton model, Morphozoic, is presented. Morphozoic may be used to
investigate the computational power of morphogenetic fields to foster the development of …

Practical and optimal reduction of watershed loads under deep uncertainty requires
sufficient search alternatives and direct evaluation of robustness. These requirements …

MANY real-world design and decision-making problems are characterized by the
interactions between decision variables. In engineering optimization problems, the effects of …