Few studies analyse the possibility of simultaneously implementing Lean Management (LM) and Green Management (GM) in the design and manage of logistic networks, specially from a quantitative perspective. This study tries to fill this gap by introducing a bi-objective model optimising lean and green aspects. NNCM (Normalized Normal Constraints Method) and Pareto frontier method are used to solve the model, by considering a mid-scale italian network. The frontier trend shows the existence of a good trade-off between LM and GM. Interestingly, the CO2 emissions decrease significantly with increasing the stock level in warehouses. The study proves that the concurrent implementation of LM and GM is a great opportunity for companies to reduce negative impacts on the environment and to increase productivity. Finally, a cost analysis is performed to evaluate which approach is more economically convenient. Results show that greater costs are associated to LM, which decrease with increasing the stocks.
Bortolini, M., Ferrari, E., Galizia, F.G., Mora, C. (2016). A bi-objective model for logistic networks design in a lean green perspective.
A bi-objective model for logistic networks design in a lean green perspective
BORTOLINI, MARCO;FERRARI, EMILIO;GALIZIA, FRANCESCO GABRIELE;MORA, CRISTINA
2016
Abstract
Few studies analyse the possibility of simultaneously implementing Lean Management (LM) and Green Management (GM) in the design and manage of logistic networks, specially from a quantitative perspective. This study tries to fill this gap by introducing a bi-objective model optimising lean and green aspects. NNCM (Normalized Normal Constraints Method) and Pareto frontier method are used to solve the model, by considering a mid-scale italian network. The frontier trend shows the existence of a good trade-off between LM and GM. Interestingly, the CO2 emissions decrease significantly with increasing the stock level in warehouses. The study proves that the concurrent implementation of LM and GM is a great opportunity for companies to reduce negative impacts on the environment and to increase productivity. Finally, a cost analysis is performed to evaluate which approach is more economically convenient. Results show that greater costs are associated to LM, which decrease with increasing the stocks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.