Special issue on advances in nature inspired algorithms for complex numerical optimization problems

Excerpt

Optimization problems occur in almost all spheres of human activities. However, with the increasing competitiveness in the real world scenario, the mathematical models of such problems are getting more and more complex. In fact, cases may appear where it become difficult to place a problem under a specific category. In order to deal with such cases, sophisticated techniques/algorithms are needed. Nature has always been a source of inspiration for researchers to develop algorithms for the complex numerical optimization problems which are usually infeasible to solve using traditional techniques. The computational algorithms inspired from nature fall under the category of Nature Inspired Algorithms (NIA). In the past few years, researchers have given much attention to NIA which not only give a reasonably good solution but are also computationally fast. Some of the popular NIA for complex numerical optimization include genetic algorithms, simulated annealing, differential evolution, particle swarm optimization, bacterial foraging optimization, artificial bee colony, neural networks, and quantum computing. The five papers included in this Special Issue are selected after a rigorous review process and at least two review rounds. Large number of high quality submissions to this Special Issue, clearly reflects the strong interest of researchers in the field of NIA. …