Document Type

Conference Paper


Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence


Business and Management., Interdisciplinary

Publication Details

12th Annual Conference of the Irish Academy of Management, Galway Mayo Institute of Technology, Galway, 2-4 September 2009


The competitiveness and dynamic nature of today’s marketplace is due to rapid advances in information technology, short product life cycles and the continuing trend in global outsourcing. Managing the resulting supply chain networks effectively is a complex and challenging task which is imputable to high level of uncertainty in supply-demand, conflict objectives, vagueness of information, numerous decision variables and constraints. With such level of complexity in the environment, supply chain optimisation has a potential to make a significant contribution to resolve the challenges. In this paper, a literature review – based on more than one hundred peer-reviewed articles – of state-of-the-art optimisation techniques in the context of supply chain management is presented. It also provides a classification of solution techniques. Linear programming, integer programming and mixed-integer programming have been used to solve many issues including; facility location, demand allocation and vehicle routing problems. The aforementioned traditional techniques have limited capabilities to handle the inherent interdependencies in supply chain networks. Such limitations of different optimisation techniques are discussed in detail. As a result, trends in current optimisation methodologies are based not only on improving a particular process performance but also on achieving a broader impact on supply chain efficiency. When properly applied, these methodologies can create precise and comprehensive models of great practical value for decision makers in managing supply chains. In such a vigorous global marketplace, supply chain optimisation is no longer an option; it is a requirement for survival to remain competitive.