A novel method to solve supplier selection problem: hybrid algorithm of genetic algorithm and ant colony optimization
type: Item
instance of: scholarly article
title: A novel method to solve supplier selection problem: hybrid algorithm of genetic algorithm and ant colony optimization
author: Jing Luan
author: Zhong Yao
author: FuTao Zhao
author: Xin Song
published in: Mathematics and Computers in Simulation
publication date: 2021-03-02T00:00:00Z
Mathematics Subject Classification ID: 90Cxx
Mathematics Subject Classification ID: 90Bxx
zbMATH DE Number: 7316580
zbMATH Keywords: supplier selection
zbMATH Keywords: hybrid algorithm
zbMATH Keywords: genetic algorithm
zbMATH Keywords: ant colony optimization
MaRDI profile type: Publication
full work available at URL: j.matcom.2018.08.011
OpenAlex ID: W2891906936
cites work: A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context
cites work: A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty
cites work: Q4079017
cites work: Select supplier-related issues in modelling a dynamic supply chain: potential, challenges and direction for future research
cites work: Type-1 and type-2 fuzzy logic controller design using a hybrid PSO-GA optimization method
cites work: Grouping genetic algorithms. Advances and applications
cites work: Supplier selection and order allocation problem using a two-phase fuzzy multi-objective linear programming
cites work: Q5315721
Wikidata QID: Q129236812
DOI: 10.1016/J.MATCOM.2018.08.011
description: scientific article; zbMATH DE number 7316580