Quantitative methods in supply chain network design and green supply chain management

2013 ◽  
Author(s):  
Ιωάννης Μαλλίδης
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Network Design ◽  
Quantitative Methods ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Chain Management

Swarm intelligence approaches in supply chain management: potentials, challenges and future research directions

2019 ◽  
Vol 24 (1) ◽  
pp. 107-123 ◽  
Author(s):  
Gunjan Soni ◽  
Vipul Jain ◽  
Felix T.S. Chan ◽  
Ben Niu ◽  
Surya Prakash
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Network Design ◽  
Optimization Problems ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Supply Chain Optimization ◽  
Chain Management ◽  
Content Type

Purpose It is worth mentioning that in supply chain management (SCM), managerial decisions are often based on optimization of resources. Till the early 2000s, supply chain optimization problems were being addressed by conventional programming approaches such as Linear Programming, Mixed-Integer Linear Programming and Branch-and-Bound methods. However, the solution convergence in such approaches was slow. But with the advent of Swarm Intelligence (SI)-based algorithms like particle swarm optimization and ant colony optimization, a significant improvement in solution of these problems has been observed. The purpose of this paper is to present and analyze the application of SI algorithms in SCM. The analysis will eventually lead to development of a generalized SI implementation framework for optimization problems in SCM. Design/methodology/approach A structured state-of-the-art literature review is presented, which explores the applications of SI algorithms in SCM. It reviews 56 articles published in peer-reviewed journals since 1999 and uses several classification schemes which are critical in designing and solving a supply chain optimization problem using SI algorithms. Findings The paper revels growth of swarm-based algorithms and seems to be dominant among all nature-inspired algorithms. The SI algorithms have been used extensively in most of the realms of supply chain network design because of the flexibility in their design and rapid convergence. Large size problems, difficult to manage using exact algorithms could be efficiently handled using SI algorithms. A generalized framework for SI implementation in SCM is proposed which is beneficial to industry practitioners and researchers. Originality/value The paper proposes a generic formulation of optimization problems in distribution network design, vehicle routing, resource allocation, inventory management and supplier management areas of SCM which could be solved using SI algorithms. This review also provides a generic framework for SI implementation in supply chain network design and identifies promising emerging issues for further study in this area.

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