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Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems–Part 2: Constrained optimization
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 …
(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
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 …
(WSA)”, which is based on two basic mechanisms,“superposition” and “attracted movement …
Fuzzy Self-tuning Bees Algorithm for designing optimal product lines
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 …
problem in marketing that aims at determining an optimal product line through which a firm …
Joint operations algorithm for large-scale global optimization
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 …
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 …
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 …
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
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 …
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 …
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
In the recent past, several biological and natural phenomena have extensively attracted
researchers towards the rapid development of science and engineering. Basically solving …
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 …
main objective of this paper is to execute new approach to obtain significant improvements …