Many optimization algorithms and metaheuristics have been inspired by nature, e.g. by the social behavior of honey bees for Artificial Bee Colony (ABC). These algorithms often permit solving a wide range of optimization problems. In this paper, we present Artificial Feeding Birds (AFB), a new metaheuristic inspired by the behavior of pigeons searching for food. AFB is very simple, yet efficient...

This paper proposes a novel hardware computing platform for fully parallel and distributed computation of artificial neural network (ANN) algorithms. The proposed idea entails leveraging the existing wireless sensor networks (WSN) technology to serve as a parallel and distributed hardware platform to implement computations for artificial neural network algorithms. Feasibility of the proposed ne...

Cell formation problem (CFP) is one of the main problems in cellular manufacturing systems. Minimizing exceptional elements and voids is one of the common objectives in the CFP. The purpose of the present study is to propose a new model for cellular manufacturing systems to group parts and machines in dedicated cells using a part-machine incidence matrix to minimize the voids. After identifying...

The idea behind this work is to solve the Shortest Common Supersequence by using Artificial Bee Colony (ABC) Algorithm. This algorithm is considered as one of the newest nature-inspired swarm-based optimization algorithms and has a promising performance [6]. Shortest Common Supersequence is a classical problem in the field of strings and it is classified as NP-Hard problem [12]. Many algorithms...

Artificial regressions are developed, based on elementary zero functions, that exploit the fact that the normal distribution is completely characterised by its first two moments. These artificial regressions can be used as the basis of numerical algorithms for the maximum likelihood estimation of models with normally distributed random elements, and other estimation techniques based on the opti...

The automatic diagnosis of breast cancer is an important, real-world medical problem. In this paper we give an introduction to fuzzy systems, genetic algorithms and artificial immune system, and then we introduce a hybrid algorithm that gathers the genetic algorithms with the artificial immune system in one algorithm. The genetic algorithm, the artificial immune system and the hybrid algorithm ...

Artificial Immune Systems (AIS) are algorithms inspired by the human immune system. The human immune system is a robust, decentralized, error tolerant and adaptive system. Such properties are highly desirable for the development of novel computer systems. Unlike some other bio-inspired techniques, such as genetic algorithms and neural networks, the field of AIS encompasses a spectrum of algorit...