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MNSWOA: A nondominated-sorting-based whale optimization algorithm for feature selection.

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MNSWOA

Introduction

This is an implementation of a multi-objective optimization algorithm called modified nondominated-sorting-based whale optimization algorithm (MNSWOA) for key quality characteristic identification (feature selection) in production processes . The optimization algorithm adapts the single objective whale optimization algorithm (WOA) into the multi-objective scenario with several new components, i.e., a modified non-dominated sorting approach, a uniform reference solution selection strategy, and mutation operations. For a detailed description of the method please refer to

Li, A.-D.*, & He, Z. (2020). Multiobjective feature selection for key quality characteristic identification in production processes using a nondominated-sorting-based whale optimization algorithm. Computers & Industrial Engineering, 149, 106852. doi:10.1016/j.cie.2020.106852 [download the bib file] [download the PDF]

Usage

  • To start with this package, just open the Main.m file with Matlab and you will find out how to use it.
  • This package is built based on the Weka, so JAVA is required in your system.

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Notes

The source code is established based on the original code of whale optimization algorithm (WOA) proposed by Prof. Seyedali Mirjalili.

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MNSWOA: A nondominated-sorting-based whale optimization algorithm for feature selection.

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