2022
DOI: 10.4018/ijamc.290541
|View full text |Cite
|
Sign up to set email alerts
|

A Novel Multi-Objective Nonlinear Discrete Binary Gaining-Sharing Knowledge-Based Optimization Algorithm

Abstract: GSK algorithm is based on the concept of how humans acquire and share knowledge through their lifespan. Discrete Binary version of GSK named novel binary Gaining Sharing knowledge-based optimization algorithm (DBGSK) depends on mainly two binary stages: binary junior gaining sharing stage and binary senior gaining sharing stage with knowledge factor 1. These two stages enable BGSK for exploring and exploitation of the search space efficiently and effectively to solve problems in binary space. Besides, one of … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 39 publications
0
2
0
Order By: Relevance
“…The resource allocation of mechanical engineering projects is a complex, changeable and dynamic multi-dimensional process with uncertainty factors. Therefore, when building the system optimization model, it is necessary to introduce multiple constraint variables to conduct comprehensive simulation analysis and evaluation of the entire system [11][12]. Figure 1…”
Section: Resource Balance Of Mechanical Engineering Projectsmentioning
confidence: 99%
“…The resource allocation of mechanical engineering projects is a complex, changeable and dynamic multi-dimensional process with uncertainty factors. Therefore, when building the system optimization model, it is necessary to introduce multiple constraint variables to conduct comprehensive simulation analysis and evaluation of the entire system [11][12]. Figure 1…”
Section: Resource Balance Of Mechanical Engineering Projectsmentioning
confidence: 99%
“…In recent years, the ENOA has been widely used due to its compatibility and practicality, and is suitable for solving non-linear optimisation problems. The algorithm does not constrain the search range, so it is more convenient and simple to handle in optimisation problems, however, due to the shortcomings of the algorithm, optimisation results are sometimes not obtained [6]. In this paper, the algorithm is used to solve a WP multi-objective optimisation problem.…”
Section: Enoamentioning
confidence: 99%