Marketing

Metaheuristic

Network planning and design

World Wide Web

Control (management)

Stochastic programming

Engineering

Supply chain network

Control engineering

Economics

Computer science

Mathematical optimization

Social network (sociolinguistics)

Risk analysis (engineering)

Management science

Business

Computer network

Physics

Operations research

Supply chain management

Mathematics

Astronomy

Social media

Chain (unit)

Supply chain

Loop (graph theory)

Artificial intelligence

Combinatorics

Closed loop

Control theory (sociology)

Applied Soft Computing

Nowadays, operation managers usually need efficient supply chain networks including important design factors such as economic and social considerations. The recent decade has seen a rapid development of controlling the uncertainty in supply chain configurations along with proposing novel solution approaches. By investigating the related studies, this paper shows that most of the current studies consider the economic aspects and just a few works present the two-stage stochastic programming as well as social considerations to design a closed-loop supply chain network. This motivated our attempts to consider economic and social aspects simultaneously by using the mentioned suppositions among the first studies. Another main contribution of this paper is the hybridization and tuning of a number of recent algorithms to address the problem. The results show that the proposed hybrid metaheuristic algorithms outperform the best existing techniques on the majority of case studies.

Multi-objective stochastic closed-loop supply chain network design with social considerations