The main focus of this paper is on the family of evolutionary algorithms and their real-life
applications. We present the following algorithms: genetic algorithms, genetic programming …

Quantum random walk is the quantum counterpart of a classical random walk. The classical
random walk concept has long been used as a computational framework for designing …

Abstract We propose hybrid Artificial Bee Colony (ABC) optimization algorithms for the well-
known Quadratic Assignment Problem (QAP). Large problem instances of the QAP are still …

This review explores the intricate and evolving relationship between Artificial Intelligence
(AI) and Quantum Computing within the realm of financial markets. As technology continues …

This paper is intended to identify the optimal number of clusters automatically from an image
dataset using some quantum behaved nature inspired meta-heuristic algorithms. Due to the …

In this paper, we present a hybrid genetic-hierarchical algorithm for the solution of the
quadratic assignment problem. The main distinguishing aspect of the proposed algorithm is …

The quadratic assignment problem (QAP) is a well‐known challenging combinatorial
optimization problem that has received many researchers' attention with varied real‐world …

This work explores the effectiveness and robustness of quantum computing by conjoining
the principles of quantum computing with the conventional computational paradigm for the …

A distributed database model can be effectively optimized through using query optimization.
In such a model, the optimizer attempts to identify the most efficient join order, which …

Query optimization is considered as the most significant part in a model of distributed
database. The optimizer tries to find an optimal join order, which reduces the query …