A survey of the nurse rostering solution methodologies: The state-of-the-art and emerging trends
This paper presents an overview of recent advances for the Nurse Rostering Problem (NRP)
based on methodological papers published between 2012 to 2021. It provides a …
based on methodological papers published between 2012 to 2021. It provides a …
Review of nature inspired metaheuristic algorithm selection for combinatorial t-way testing
The metaheuristic algorithm is a very important area of research that continuously improves
in solving optimization problems. Nature-inspired is one of the metaheuristic algorithm …
in solving optimization problems. Nature-inspired is one of the metaheuristic algorithm …
The hybrid harris hawks optimizer-arithmetic optimization algorithm: a new hybrid algorithm for sizing optimization and design of microgrids
This paper presents a new hybrid metaheuristic algorithm, the hybrid Harris Hawks
Optimizer-Arithmetic Optimization Algorithm (hHHO-AOA), as we have named it. It is …
Optimizer-Arithmetic Optimization Algorithm (hHHO-AOA), as we have named it. It is …
Q-learnheuristics: Towards data-driven balanced metaheuristics
B Crawford, R Soto, J Lemus-Romani… - Mathematics, 2021 - mdpi.com
One of the central issues that must be resolved for a metaheuristic optimization process to
work well is the dilemma of the balance between exploration and exploitation. The …
work well is the dilemma of the balance between exploration and exploitation. The …
Construction of prioritized T-way test suite using bi-objective dragonfly algorithm
Software testing is important for ensuring the reliability of software systems. In software
testing, effective test case generation is essential as an alternative to exhaustive testing. For …
testing, effective test case generation is essential as an alternative to exhaustive testing. For …
[HTML][HTML] Gravitational search algorithm based strategy for combinatorial t-way test suite generation
Due to different users' requirements, contemporary software has become feature-rich in
terms of input functions (ie, parameters) and selections (ie, values). Exhaustive testing on …
terms of input functions (ie, parameters) and selections (ie, values). Exhaustive testing on …
[PDF][PDF] Whale Optimization Algorithm Strategies for Higher Interaction Strength T-Way Testing.
Much of our daily tasks have been computerized by machines and sensors communicating
with each other in real-time. There is a reasonable risk that something could go wrong …
with each other in real-time. There is a reasonable risk that something could go wrong …
A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search‐Based Software Engineering
Swarm intelligence algorithms are metaheuristics inspired by the collective behavior of
species such as birds, fish, bees, and ants. They are used in many optimization problems …
species such as birds, fish, bees, and ants. They are used in many optimization problems …
Hybrid henry gas solubility optimization algorithm with dynamic cluster-to-algorithm mapping
This paper discusses a new variant of Henry Gas Solubility Optimization (HGSO) Algorithm,
called Hybrid HGSO (HHGSO). Unlike its predecessor, HHGSO allows multiple clusters …
called Hybrid HGSO (HHGSO). Unlike its predecessor, HHGSO allows multiple clusters …
An Experimental Study of a Fuzzy Adaptive Emperor Penguin Optimizer for Global Optimization Problem
Emperor Penguin Optimizer (EPO) is a recently developed population-based meta-heuristic
algorithm that simulates the huddling behavior of emperor penguins. Mixed results have …
algorithm that simulates the huddling behavior of emperor penguins. Mixed results have …