14 papers · ranked by Valyu relevance
He Li, Naiyu Shi
In order to address the application of genetic optimization algorithms to financial investment portfolio issues, the optimal allocation rate must be high and the risk is low. This paper uses quadratic programming algorithms and genetic algorithms as well as quadratic programming algorithms, Matlab planning solutions…
Panagiotis Aivaliotis-Apostolopoulos, Dimitrios Loukidis, Seyedali Mirjalili
'Seyedali Mirjalili'] Particle swarm optimization and genetic algorithms are two classes of popular heuristic algorithms that are frequently used for solving complex multi-dimensional mathematical optimization problems, each one with its one advantages and shortcomings. Particle swarm optimization is known to favor…
Kara Layne Johnson, Nicole Bohme Carnegie
Genetic algorithms mimic the process of natural selection in order to solve optimization problems with minimal assumptions and perform well when the objective function has local optima on the search space. These algorithms treat potential solutions to the optimization problem as chromosomes, consisting of genes which…
L. Jayakumar, R. Jothi Chitra, J. Sivasankari, S. Vidhya + 6 more
'Laura Alimzhanova' 'Gulnur Kazbekova' 'Bakhytzhan Kulambayev' 'Alma Kostangeldinova' 'S. Devi' 'Dawit Mamiru Teressa'] This work explains why and how QoS modeling has been used within a multicriteria optimization approach. The parameters and metrics defined are intended to provide a broader and, at the same time, more…
Junyu Zhang, Pengyuan Qi, Jike Wang, S. Svensson
A universal optimization simulation method based on a multi-objective genetic algorithm is introduced; this is the first attempt to optimize the elements of a beamline using this method.
Zenghua Chen, Lingjian Zhu, He Lu, Shichao Chen + 4 more
'Sheng Liu' 'Yunjun Han' 'Gang Xiong'] Health monitoring and fault diagnosis of rolling bearings are crucial for the continuous and effective operation of mechanical equipment. In order to improve the accuracy of BP neural network in fault diagnosis of rolling bearings, a feature model is established from the vibration…
Seyed Hayan Zaheri, Mahdi Hosseini, Mohammad Fathinasab
Determination of optimum well location and operational settings for existing and new wells is crucial for maximizing production in field development. These optimum conditions depend on geological and petrophysical factors, fluid flow regimes, and economic variables. However, conducting numerous simulations for various…
Ahmed Redha Mahlous, Houssam Mahlous, Yilun Shang
Universities face a constant challenge when distributing students and allocating them to their required classes, especially for a large mass of students. Generating feasible timetables is a strenuous task that requires plenty of resources, which makes it impractical to take student preferences into consideration during…
Tiantian Mi
Laboratory equipment planning is a very important task in modern enterprise management. Laboratory equipment planning by computer algorithm is a very complex NP-hard combinatorial optimization problem, so it is impossible to find an accurate algorithm in polynomial time. In this study, an improved genetic algorithm is…
Rashad Moqa, Irfan Younas, Maryam Bashir, Seyedali Mirjalili
The first step in Genetic Algorithms (GAs) is to initialize a set of chromosomes as the initial population. The initialization usually generates chromosomes randomly. Conventional multi-objective GAs result in candidate solutions being gathered close to the middle of the objective space. An initialization based on the…
Yingxin Sun
In order to make key decisions more conveniently according to the massive data information obtained, a spatial data mining technology based on a genetic algorithm is proposed, which is combined with the k-means algorithm. The immune principle and adaptive genetic algorithm are introduced to optimize the traditional…
Sizhe Yuen, Thomas H. G. Ezard, Adam J. Sobey
Evolutionary computation is a group of biologically inspired algorithms used to solve complex optimization problems. It can be split into evolutionary algorithms, which take inspiration from genetic inheritance, and swarm intelligence algorithms, that take inspiration from cultural inheritance. However, much of the…
Alexander Lalejini, Emily Dolson, Anya E Vostinar, Luis Zaman + 2 more
'C Brandon Ogbunugafor' 'Christian R Landry'] Directed microbial evolution harnesses evolutionary processes in the laboratory to construct microorganisms with enhanced or novel functional traits. Attempting to direct evolutionary processes for applied goals is fundamental to evolutionary computation, which harnesses…
Kosuke Hamazaki, Hiroyoshi Iwata
Emerging technologies such as genomic selection have been applied to modern plant and animal breeding to increase the speed and efficiency of variety release. However, breeding requires decisions regarding parent selection and mating pairs, which significantly impact the ultimate genetic gain of a breeding scheme. The…