Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition

European Journal of Operational Research

Volumn 249, Issue 1, 2016, Pages 76-92

  Keyvanshokooh, Esmaeil ^a   Ryan, Sarah M ^b   Kabir, Elnaz ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

^b Iowa State University of Science and Technology   (United States)

Author keywords

Benders decomposition; Closed loop supply chain; Robust optimization; Robustness and sensitivity analysis; Stochastic programming

Indexed keywords

PARETO PRINCIPLE; SENSITIVITY ANALYSIS; STOCHASTIC MODELS; STOCHASTIC PROGRAMMING; STOCHASTIC SYSTEMS; SUPPLY CHAINS;

BENDERS DECOMPOSITION; BENDERS DECOMPOSITION ALGORITHM; CLOSED-LOOP SUPPLY CHAIN; CLOSED-LOOP SUPPLY CHAIN NETWORK DESIGNS; CLOSED-LOOP SUPPLY CHAIN NETWORKS; LATIN HYPERCUBE SAMPLING METHODS; ROBUST OPTIMIZATION; ROBUSTNESS AND SENSITIVITY ANALYSIS;

INTEGER PROGRAMMING;

EID: 84948675984     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2015.08.028     Document Type: Article

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