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A conceptual framework for modelling reverse logistics networks

A conceptual framework for modelling reverse logistics networks Reverse logistics is receiving more attention because of the growing environmental and economical concerns. Some complex issues depending on social, technical and legislative factors are: how to prevent the environmental deterioration caused by the generation of wastes, how to minimise the generation of wastes, and how to enhance the value recovery from the wastes. In this paper, we have done an exhaustive literature review, highlighting the applications of various modelling approaches from reverse logistics perspectives. The considered modelling approaches are linear programming, mixed integer linear programming, goal programming and genetic algorithm. The reverse logistics issues are basically categorised into five categories namely distribution, production planning and control, information technology, business economics and integration/coordination. The paper proposes a framework focusing these issues and suggests an appropriate approach to model reverse logistics networks. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Business Performance and Supply Chain Modelling Inderscience Publishers

A conceptual framework for modelling reverse logistics networks

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1758-9401
eISSN
1758-941X
DOI
10.1504/IJBPSCM.2011.043835
Publisher site
See Article on Publisher Site

Abstract

Reverse logistics is receiving more attention because of the growing environmental and economical concerns. Some complex issues depending on social, technical and legislative factors are: how to prevent the environmental deterioration caused by the generation of wastes, how to minimise the generation of wastes, and how to enhance the value recovery from the wastes. In this paper, we have done an exhaustive literature review, highlighting the applications of various modelling approaches from reverse logistics perspectives. The considered modelling approaches are linear programming, mixed integer linear programming, goal programming and genetic algorithm. The reverse logistics issues are basically categorised into five categories namely distribution, production planning and control, information technology, business economics and integration/coordination. The paper proposes a framework focusing these issues and suggests an appropriate approach to model reverse logistics networks.

Journal

International Journal of Business Performance and Supply Chain ModellingInderscience Publishers

Published: Jan 1, 2011

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