COVID-19 cases prediction by using hybrid machine learning and beetle antennae search approach
The main objective of this paper is to further improve the current time-series prediction
(forecasting) algorithms based on hybrids between machine learning and nature-inspired …
(forecasting) algorithms based on hybrids between machine learning and nature-inspired …
Improved bat algorithm applied to multilevel image thresholding
Multilevel image thresholding is a very important image processing technique that is used as
a basis for image segmentation and further higher level processing. However, the required …
a basis for image segmentation and further higher level processing. However, the required …
[PDF][PDF] Artificial bee colony algorithm hybridized with firefly algorithm for cardinality constrained mean-variance portfolio selection problem
Portfolio selection (optimization) problem is a very important and widely researched problem
in the areas of finance and economy. Literature review shows that many methods and …
in the areas of finance and economy. Literature review shows that many methods and …
Firefly Algorithm for Cardinality Constrained Mean‐Variance Portfolio Optimization Problem with Entropy Diversity Constraint
Portfolio optimization (selection) problem is an important and hard optimization problem that,
with the addition of necessary realistic constraints, becomes computationally intractable …
with the addition of necessary realistic constraints, becomes computationally intractable …
Improved seeker optimization algorithm hybridized with firefly algorithm for constrained optimization problems
Seeker optimization algorithm is one of the recent swarm intelligence metaheuristics for hard
optimization problems. It is based on the human group search behavior and it was …
optimization problems. It is based on the human group search behavior and it was …
Cuckoo search and firefly algorithm applied to multilevel image thresholding
Multilevel image thresholding is a technique widely used in image processing, most often for
segmentation. Exhaustive search is computationally prohibitively expensive since the …
segmentation. Exhaustive search is computationally prohibitively expensive since the …
A grey wolf optimization approach for improving the performance of wireless sensor networks
Optimizing the energy consumption of sensor nodes have been a big design issue in
wireless sensor networks (WSNs). Energy efficient WSN usually compromise with network …
wireless sensor networks (WSNs). Energy efficient WSN usually compromise with network …
A greedy randomized adaptive search procedure (GRASP) for minimum 2-fold connected dominating set problem
X Nie, Q Zhang, Y Qiao, Z Qi, L Zhang, D Niu… - Applied Soft …, 2024 - Elsevier
The minimum 2-fold connected dominating set problem (M (2-fold) CDSP) is an important
variant of the traditional minimum connected dominating set problem (MCDSP), with crucial …
variant of the traditional minimum connected dominating set problem (MCDSP), with crucial …
Dynamic vehicle routing with time windows in theory and practice
The vehicle routing problem is a classical combinatorial optimization problem. This work is
about a variant of the vehicle routing problem with dynamically changing orders and time …
about a variant of the vehicle routing problem with dynamically changing orders and time …
Improved ACO algorithm with pheromone correction strategy for the traveling salesman problem
A new, improved ant colony optimization (ACO) algorithm with novel pheromone correction
strategy is introduced. It is implemented and tested on the traveling salesman problem …
strategy is introduced. It is implemented and tested on the traveling salesman problem …