This study analyses the mixed-integer linear program (MILP) proposed by Kannan etal. [Kannan, G., Noorul Hag, A., and Devika, M., 2009. Analysis of closed loop supply chain using genetic algorithm and particle swarm optimization. International Journal of Production Research, 47 (5), 1175-1200] in their paper entitled Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation. Since we find inconsistencies in the model, we propose modifications to rectify the flaws. The revised model is presented and tested using a hypothetical problem. © 2012 Copyright Taylor and Francis Group, LLC.

T. T. Narendran

Closed-loop supply chain

Data sets

International journals

Mixed integer linear program

Particle swarm optimisation

PRODUCTION RESEARCH

SUPPLY CHAIN MODELS

Technical notes

Genetic algorithms

Integer programming

Mathematical models

Particle swarm optimization (PSO)

Supply chains

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

A technical note on ‘Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation’

International Journal of Production Research

Concerns over environmental degradation legislative requirements and growing business needs have fueled the growth of closed-loop supply chains (CLSCs). This paper addresses a bi-objective network design problem for multi-period, multi-product CLSC to minimize the total supply chain costs and to maximize the service efficiency of the warehouses and hybrid facilities. We develop a bi-objective mixed integer linear programming model to assist decisions in (1) location/ operating decisions for warehouses, hybrid facilities and manufacturing facilities and (2) production and distribution of products between stages in the supply chain. Goal programming models and compromise programming techniques are used to solve the problem. An application of the model is demonstrated using a case study from the literature. ©2013 Chinese Institute of Industrial Engineers.

Journal of Industrial and Production Engineering

A bi-objective network design model for multi-period, multi-product closed-loop supply chain

Concerns over environmental degradation, legislative requirements and growing needs of business have fueled the growth of Closed Loop Supply Chains (CLSC). We consider a CLSC and address the issues of designing the network and of optimizing the distribution. Four variants of the problem are considered. The problem is modeled as an Integer Linear Program (ILP). We develop a constructive heuristic based on Vogel's approximation method-total opportunity cost method to provide good initial solutions to a priority-based simulated annealing heuristic, to accelerate its convergence. Trials on a set of hypothetical datasets have yielded encouraging results. The methodology is also tested using a case study data of a company producing electronic products. Implications for sustainability are discussed. © 2012 Elsevier B.V. All rights reserved.

Applied Soft Computing Journal

PRISM: PRIority based SiMulated annealing for a closed loop supply chain network design problem

A technical note on Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation

Journal	International Journal of Production Research
ISSN	00207543
Open Access	No