Sustainable supplier selection and order allocation: A novel multi-objective programming model with a hybrid solution approach

2019 ◽  
Vol 129 ◽  
pp. 192-209 ◽  
Author(s):  
Hadi Moheb-Alizadeh ◽  
Robert Handfield
Keyword(s):  
Supplier Selection ◽  
Programming Model ◽  
Order Allocation ◽  
Solution Approach ◽  
Multi Objective ◽  
Multi Objective Programming ◽  
Sustainable Supplier Selection ◽  
Hybrid Solution ◽  
Objective Programming

scholarly journals A New Integrated Multi-Criteria Decision Making and Multi-Objective Programming Model for Sustainable Supplier Selection and Order Allocation

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 302 ◽  
Author(s):  
Shan-Yong You ◽  
Li-Jun Zhang ◽  
Xue-Guo Xu ◽  
Hu-Chen Liu
Keyword(s):  
Supplier Selection ◽  
Programming Model ◽  
Critical Role ◽  
Optimal Order ◽  
Order Allocation ◽  
Multi Objective ◽  
Sustainable Performance ◽  
Multi Objective Programming ◽  
Sustainable Supplier Selection ◽  
Order Quantities

With the increasing pressure from global competition, manufacturers have realized that sustainable production is significant in supply chain management. Sustainable supplier selection and order allocation (SSS&OA) play a distinct and critical role for organizations to achieve sustainable development and build competitive advantage. In this paper, we aim to develop a novel SSS&OA model for selecting the most suitable sustainable suppliers and determining the optimal order sizes among them. First, double hierarchy hesitant linguistic term sets (DHHLTSs) are adopted to deal with uncertainty in evaluating the sustainable performance of alternative suppliers. Then, an extended decision field theory is proposed to choose efficient sustainable suppliers dynamically. Considering quantity discount, a multi-objective linear programming (MOLP) model is established to allocate reasonable order quantities among the selected suppliers. Finally, the applicability and effectiveness of the developed model are illustrated through its application in the electronic industry and through a comparative analysis with other methods.

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