The optimization problems are becoming more complicated, requiring new and efficient
optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have …

Over past few decades, families of algorithms based on the intelligent group behaviors of
social creatures like ants, birds, fishes, and bacteria have been extensively studied and …

The artificial bee colony (ABC) algorithm is a swarm-based optimization technique proposed
for solving continuous optimization problems. The artificial agents of the ABC algorithm use …

This paper presents a novel hybrid algorithm (TABC) that combines the artificial bee colony
(ABC) and tabu search (TS) to solve the hybrid flow shop (HFS) scheduling problem with …

This article investigates how to employ artificial bee colony algorithm to solve Set-Union
Knapsack Problem (SUKP). A mathematical model of SUKP, which is to be easily solved by …

One of the major optimization problems in power systems is the optimal reactive power
dispatch (ORPD) problem. ORPD problem is a multi-variable problem with non-linear …

Metaheuristic algorithms have been successfully used to parameter identification of
photovoltaic systems. However, this still faces the following two challenges. Firstly, most of …

Recently, optimization makes an important role in our day-to-day life. Evolutionary and
population-based optimization algorithms are widely employed in several of engineering …

Artificial bee colony (ABC) algorithm represents one of the most-studied swarm intelligence
algorithms. Since the original ABC has been found to be very effective, today there are a lot …

Cluster analysis is important in data mining, especially if there is unsupervised data.
Recently, many clustering methods have been proposed. Unfortunately, most of these …