Abstract
The aim of the present paper is to provide an application to a real-life supply-chain context (i.e. the Pirelli Tyre European logistics network) of an integrated logistics network design and optimisation model. Starting from the analysis of supply chain under study and of the configuration problem to be solved, we identified the most suitable approach: a mixed integer linear programming optimisation model endowed with a series of guidelines for gathering and processing all the data necessary to set-up and run the model. The application of the selected integrated design and optimisation model to the Pirelli Tyre case led to significant cost savings related to three different service-level scenarios. Thus, the applied model could be profitably implemented by supply chain and logistics managers for optimising various operating contexts. Moreover, the exemplified data-mapping section represents a useful guideline, which can be applied by practitioners to gather and handle the high volume of data necessary for running the model in a real-life context. In conclusion, since the current state of the art is particularly lacking exhaustive supply-chain design models, the implemented integrated approach represents a significant contribution to the existing body of knowledge on supply chain configuration.
Highlights
Introduction and backgroundIn recent years supply chains have witnessed a restless evolution, due to impressive changes of the world economy and of the competitive environment
Starting from the analysis of supply chain under study and of the configuration problem to be solved, we identified the most suitable approach: a mixed integer linear programming optimisation model endowed with a series of guidelines for gathering and processing all the data necessary to set-up and run the model
The aim of the present paper is to provide an application to a real life supply chain context of an integrated logistics network design and optimisation model
Summary
In recent years supply chains have witnessed a restless evolution, due to impressive changes of the world economy and of the competitive environment. Notwithstanding its limitations, its wide adoption and use are due to the fact that it allows for developing solvers, which enable solutions for the network configuration problems to be obtained, taking into account a series of objectives and constraints (Sharma, 2006) This kind of solvers can be implemented by means of spreadsheet software packages, so as they can be used in a very effective way for analysing logistics and supply chain issues and creating different scenarios for deriving the optimal values of variables such as, for instance, facility number and size (Smith, 2003). A series of concluding remarks and managerial implications deriving from the present study are discussed in paragraph 5
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