This paper presents a review of quantum-inspired population-based metaheuristics.
Quantum-inspired algorithms were born when there were no quantum computers; they …

Abstract Association Rule Mining (ARM) is a significant task for discovering frequent patterns
in data mining. It has achieved great success in a plethora of applications such as market …

Particle swarm optimization (PSO) is predominately used to find solutions for continuous
optimization problems. As the operators of PSO are originally designed in an n-dimensional …

The vector quantization (VQ) was a powerful technique in the applications of digital image
compression. The traditionally widely used method such as the Linde–Buzo–Gray (LBG) …

Quantum-inspired evolutionary algorithms, one of the three main research areas related to
the complex interaction between quantum computing and evolutionary algorithms, are …

In this paper, a binary version of equilibrium optimization (BEO) is proposed for the tackling
0–1 knapsack problem characterized as a discrete problem. Because the standard …

The field of natural computing has been the focus of a substantial research effort in recent
decades. One particular strand of this concerns the development of computational …

Natural phenomenon can be used to solve complex optimization problems with its excellent
facts, functions, and phenomenon. In this paper, a survey on physics‐based algorithm is …

The Resource-Constrained Project-Scheduling Problem (RCPSP) is an NP-hard problem
which can be found in many research domains. The optimal solution of the RCPSP …

Abstract Linde–Buzo–Gray (LBG), a traditional method of vector quantization (VQ) generates
a local optimal codebook which results in lower PSNR value. The performance of vector …