An Improved Artificial Electric Field Algorithm for Multi-Objective Optimization
Real-world problems such as scientific, engineering, mechanical, etc., are multi-objective optimization problems. In order to achieve an optimum solution to such problems, multi-objective optimization algorithms are used. A solution to a multi-objective problem is to explore a set of candidate solut...
Main Authors: | Hemant Petwal, Rinkle Rani |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-05-01
|
Series: | Processes |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-9717/8/5/584 |
Similar Items
-
Fine-Grained Ensemble of Evolutionary Operators for Objective Space Partition Based Multi-Objective Optimization
by: Xuefeng Hong, et al.
Published: (2021-01-01) -
An Efficient Clustering Algorithm for Mixed Dataset of Postoperative Surgical Records
by: Hemant Petwal, et al.
Published: (2020-06-01) -
Pareto Dominance-Based Algorithms With Ranking Methods for Many-Objective Optimization
by: Vikas Palakonda, et al.
Published: (2017-01-01) -
A Knowledge-Informed and Pareto-Based Artificial Bee Colony Optimization Algorithm for Multi-Objective Land-Use Allocation
by: Lina Yang, et al.
Published: (2018-02-01) -
Relevance of Multi-Objective Optimization in the Chemical Engineering Field
by: Cáceres Sepúlveda, Geraldine
Published: (2019)