An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization


Evolutionary algorithms are shown to be powerful for solving multiobjective optimization issues, in that nondominated sorting could be a widely adopted technique in selection. This technique, but, can be computationally expensive, especially when the number of individuals in the population becomes giant. This can be mainly because in most existing nondominated sorting algorithms, a resolution wants to be compared with all alternative solutions before it will be assigned to a front. During this paper we tend to propose a completely unique, computationally efficient approach to nondominated sorting, termed efficient nondominated type (ENS). In ENS, a solution to be assigned to a front needs to be compared only with those who have already been assigned to a front, thereby avoiding many unnecessary dominance comparisons. Based mostly on this new approach, 2 nondominated sorting algorithms are prompt. Both theoretical analysis and empirical results show that the ENS-based mostly sorting algorithms are computationally more economical than the state-of-the-art nondominated sorting methods.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : TARA: An Efficient Random Access Mechanism for NB-IoT by Exploiting TA Value Difference in Collided Preambles ABSTRACT: The 3rd Generation Partnership Project (3GPP) has specified the narrowband Internet of Things
PROJECT TITLE : ESVSSE Enabling Efficient, Secure, Verifiable Searchable Symmetric Encryption ABSTRACT: It is believed that symmetric searchable encryption, also known as SSE, will solve the problem of privacy in data outsourcing
PROJECT TITLE : ESA-Stream: Efficient Self-Adaptive Online Data Stream Clustering ABSTRACT: A wide variety of big data applications generate an enormous amount of streaming data that is high-dimensional, real-time, and constantly
PROJECT TITLE : Efficient Shapelet Discovery for Time Series Classification ABSTRACT: Recently, it was discovered that time-series shapelets, which are discriminative subsequences, are effective for the classification of time
PROJECT TITLE : Efficient Identity-based Provable Multi-Copy Data Possession in Multi-Cloud Storage ABSTRACT: A significant number of clients currently store multiple copies of their data on a variety of cloud servers. This helps

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry