Clustering and selecting suppliers based on simulated annealing algorithms

DOI10.1016/j.camwa.2011.11.014zbMath1238.90013OpenAlexW2063038380MaRDI QIDQ418322

J. Herrera, H. S. Yoon

Publication date: 28 May 2012

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2011.11.014

zbMATH Keywords

analytic hierarchy processTaguchi methodsimulated annealing\(K\)-meanssupplier selectionsupplier clustering

Mathematics Subject Classification ID

Transportation, logistics and supply chain management (90B06)

Related Items (2)

Tiered Data Envelopment as method for clustering suppliers ⋮ Fast global \(k\)-means clustering based on local geometrical information

Cites Work

• Optimization by Simulated Annealing
• An optimization approach for supply chain management models with quantity discount policy
• A multi-objective production scheduling case study solved by simulated annealing
• Vendor selection in outsourcing
• Using fuzzy analytic hierarchy process and particle swarm optimisation for balanced and defective supply chain problems considering WEEE/RoHS directives
• Supply chain network design: partner selection and production/distribution planning using a systematic model
• A multi-phase model for product part change problems
• On clustering validation techniques

This page was built for publication: Clustering and selecting suppliers based on simulated annealing algorithms