A genetic algorithm approach for multi-objective optimization of supply chain networks
By Fulya Altıparmak, Mitsuo Gen, Lin Lin, Turan Paksoy. Computers & industrial engineering, 2006
635 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Management Information Systems, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/3134a760e5ebe6a62858d800de9e66d68871cc1c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
In Management Information Systems
- Francisco Saldanha-da-Gama
- Wei-Chang Yeh
- Stefan Nickel
- Mei-Chi Chuang
- Pejvak Oghazi
- Youfang Huang
- Jovin J. Mwemezi
In Strategy and Management
- Stefan Nickel
- Ali Nazarpour
- Francisco Saldanha-da-Gama
- Wei-Chang Yeh
- Reza Toorajipour
- Mei-Chi Chuang
- Pejvak Oghazi
- Maria Fischl
Citations in the corpus
- Using multi-objective genetic algorithm for partner selection in green supply chain problems (2011, methodology): “The crossover mechanism of MOGA_2 (Altiparmak et al., 2006). ig.”
- Facility location and supply chain management - A review (2009, background): “The terms network design and supply chain network design (SCND) are sometimes employed as synonyms of strategic supply chain planning (see [3,18,75,113]).”
- Artificial intelligence in supply chain management: A systematic literature review (2021, positive): “GAs have become a popular technique due to its applicability to multi-objective optimisation of supply chain networks (Altiparmak et al., 2006), partner selection in green supply chain problems (Yeh and Chuang, 2011), multi-product supply chain networks (Altiparmak et al., 2009) and the…”