Multi-population techniques in nature inspired optimization algorithms: A comprehensive survey
Multi-population based nature-inspired optimization algorithms have attracted wide research
interests in the last decade, and become one of the frequently used methods to handle real …
interests in the last decade, and become one of the frequently used methods to handle real …
The application of artificial intelligence in project management research: A review
The field of artificial intelligence is currently experiencing relentless growth, with
innumerable models emerging in the research and development phases across various …
innumerable models emerging in the research and development phases across various …
A modified covariance matrix adaptation evolution strategy for real-world constrained optimization problems
Most of the real-world black-box optimization problems are associated with multiple non-
linear as well as non-convex constraints, making them difficult to solve. In this work, we …
linear as well as non-convex constraints, making them difficult to solve. In this work, we …
Building energy consumption forecast using multi-objective genetic programming
A Tahmassebi, AH Gandomi - Measurement, 2018 - Elsevier
A multi-objective genetic programming (MOGP) technique with multiple genes is proposed
to formulate the energy performance of residential buildings. Here, it is assumed that loads …
to formulate the energy performance of residential buildings. Here, it is assumed that loads …
Empirical linkage learning
MW Przewozniczek, MM Komarnicki - Proceedings of the 2020 Genetic …, 2020 - dl.acm.org
Linkage learning is employed by many state-of-the-art evolutionary methods designed for
solving problems in discrete domains. The effectiveness of these methods is dependent on …
solving problems in discrete domains. The effectiveness of these methods is dependent on …
A multipopulation-based multiobjective evolutionary algorithm
Multipopulation is an effective optimization component often embedded into evolutionary
algorithms to solve optimization problems. In this paper, a new multipopulation-based …
algorithms to solve optimization problems. In this paper, a new multipopulation-based …
Multi-Objective parameter-less population pyramid for solving industrial process planning problems
Evolutionary methods are effective tools for obtaining high-quality results when solving hard
practical problems. Linkage learning may increase their effectiveness. One of the state-of …
practical problems. Linkage learning may increase their effectiveness. One of the state-of …
Scalable distributed evolutionary algorithm orchestration using Docker containers
In smart factories, integrated optimisation of manufacturing process planning and scheduling
leads to better results than a traditional sequential approach but is computationally more …
leads to better results than a traditional sequential approach but is computationally more …
Cloud-based dynamic distributed optimisation of integrated process planning and scheduling in smart factories
In smart factories, process planning and scheduling need to be performed every time a new
manufacturing order is received or a factory state change has been detected. A new plan …
manufacturing order is received or a factory state change has been detected. A new plan …
Towards solving practical problems of large solution space using a novel pattern searching hybrid evolutionary algorithm–an elastic optical network optimization case …
The fast social and economic development observed in the recent years brings up new
challenging optimization problems. These problems are often very hard not only because of …
challenging optimization problems. These problems are often very hard not only because of …