Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems–Part 2: Constrained optimization

A Baykasoğlu, Ş Akpinar - Applied Soft Computing, 2015 - Elsevier
This paper is the second one of the two papers entitled “Weighted Superposition Attraction
(WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in …

Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems–Part 1: Unconstrained optimization

A Baykasoğlu, Ş Akpinar - Applied Soft Computing, 2017 - Elsevier
This paper is the first one of the two papers entitled “Weighted Superposition Attraction
(WSA)”, which is based on two basic mechanisms,“superposition” and “attracted movement …

Fuzzy Self-tuning Bees Algorithm for designing optimal product lines

K Zervoudakis, S Tsafarakis - Applied Soft Computing, 2024 - Elsevier
Abstract The Product Line Design (PLD) problem is an NP-hard combinatorial optimization
problem in marketing that aims at determining an optimal product line through which a firm …

Joint operations algorithm for large-scale global optimization

G Sun, R Zhao, Y Lan - Applied Soft Computing, 2016 - Elsevier
Large-scale global optimization (LSGO) is a very important but thorny task in optimization
domain, which widely exists in management and engineering problems. In order to …

Enhancing the Bees Algorithm using the traplining metaphor

AH Ismail - 2021 - etheses.bham.ac.uk
This work aims to improve the performance of the Bees Algorithm (BA), particularly in terms
of simplicity, accuracy, and convergence. Three improvements were made in this study as a …

[HTML][HTML] Enhanced swarm intelligence optimization: Inspired by cellular coordination in immune systems

B Liu, M Xu, L Gao - Knowledge-Based Systems, 2024 - Elsevier
Swarm intelligence optimization algorithms (SIOAs) are widely used to address complex
problems but often trapped in local optima. To overcome this, we propose a novel multi …

[PDF][PDF] Overview of parallel computing for meta-heuristic algorithms

Y Sun, SC Chu, P Hu, J Watada, M Si, JS Pan - J. Netw. Intell, 2022 - bit.kuas.edu.tw
The meta-heuristic algorithm is used in the research of various complex problems. Due to
the limitations of the original meta-heuristic algorithm, many improved meta-heuristic …

A modified surrogate-assisted multi-swarm artificial bee colony for complex numerical optimization problems

L Sun, W Sun, X Liang, M He, H Chen - Microprocessors and Microsystems, 2020 - Elsevier
Artificial bee colony (ABC) algorithm has been widely used in solving complex optimization
due to its few control parameters and outstanding global search capability. However, ABC …

A novel honey-bees mating optimization approach with higher order neural network for classification

J Nayak, B Naik - Journal of Classification, 2018 - Springer
In the recent past, several biological and natural phenomena have extensively attracted
researchers towards the rapid development of science and engineering. Basically solving …

A new wolf colony search algorithm based on search strategy for solving travelling salesman problem

Y Sun, L Teng, S Yin, H Li - International Journal of …, 2019 - inderscienceonline.com
Though many intelligence algorithms are used for travelling salesman problem (TSP), the
main objective of this paper is to execute new approach to obtain significant improvements …