An integrated data envelopment analysis–mathematical programming approach to strategic biodiesel supply chain network design problem

2017 ◽  
Vol 147 ◽  
pp. 694-707 ◽  
Author(s):  
Reza Babazadeh ◽  
Jafar Razmi ◽  
Masoud Rabbani ◽  
Mir Saman Pishvaee
2021 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrică C Pop ◽  
Cosmin Sabo

Abstract In this paper we investigate a particular two-stage supply chain network design problem with fixed costs. In order to solve this complex optimization problem, we propose an efficient hybrid algorithm, which was obtained by incorporating a linear programming optimization problem within the framework of a genetic algorithm. In addition, we integrated within our proposed algorithm a powerful local search procedure able to perform a fine tuning of the global search. We evaluate our proposed solution approach on a set of large size instances. The achieved computational results prove the efficiency of our hybrid genetic algorithm in providing high-quality solutions within reasonable running-times and its superiority against other existing methods from the literature.


2017 ◽  
Vol 254 (1-2) ◽  
pp. 533-552 ◽  
Author(s):  
Xiaoge Zhang ◽  
Andrew Adamatzky ◽  
Felix T. S. Chan ◽  
Sankaran Mahadevan ◽  
Yong Deng

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