Regional low-carbon timber logistics network design and management using multi-objective optimization Academic Article uri icon

abstract

  • 2017 The Japanese Forest Society. With the concern about environmental issues, supply chain designers and managers need to make trade-offs between the environmental impacts and costs of a logistics network. We develop a multi-objective optimization model that minimizes the total cost and CO2 emissions of a regional timber logistics network and seeks for the simultaneous optimization of logistics network design and operation. The generic model is applied to a case study in Jiangle County in China. The Pareto solution set, derived by applying the normalized normal constraint method, shows the relationship between carbon emissions and total cost. Our results reveal that both network structure and the allocations of timber flows have effects on the Pareto solutions, suggesting the importance of considering network design and management together in logistics network analysis. The model results also indicate that though the current carbon price is hard to trigger the change of the timber logistics network structure in Jiangle County, it can still be a driving force to push the decision-makers to implement lower carbon logistics plans. Additionally, sensitivity analysis shows that improving road conditions can remarkably reduce CO2 emissions in the logistics network and that maintaining an appropriate ratio of timber supply to demand can lead to some compromise between carbon emissions and total cost. These findings offer new insights into the trade-offs between the carbon emissions and total cost of the regional timber logistics network, which are of value to logistics network designers and managers as well as policy-makers in the study region and beyond.

published proceedings

  • JOURNAL OF FOREST RESEARCH

author list (cited authors)

  • Chen, C., Hu, X., Gan, J., & Qiu, R.

citation count

  • 5

complete list of authors

  • Chen, Cheng||Hu, Xisheng||Gan, Jianbang||Qiu, Rongzu

publication date

  • November 2017