多溫層食品運輸排程與溫室氣體排放研究

Abstract

In light of the demand for high-quality fresh food, transportation requirements for fresh food delivery have been continuously increasing in urban areas. Jointly delivering foods with different temperature-control requirements is an important issue for urban logistic carriers who transport both low temperature-controlled foods and normal merchandise. On the other hand, sources of greenhouse gas (GHG) emissions related to food transportation include energy consumption and refrigerant leakage. HFCs and PFCs generated by refrigerant leakage markedly increase global warming potential (GWP), and many governments around the world have developed futures markets for emission allowances or levied carbon taxes. Given this, how to deliver multi-temperature food considering GHG emissions has become an important issue for carriers. This dissertation aims to analyze and optimize medium-term planning and short-term operation for multi-temperature food transportation. Moreover, this dissertation explores greenhouse gas emissions from multi-temperature food delivery. For medium-term planning, this dissertation optimizes fleet size for carriers considering time-dependent multi-temperature food demand. For short-term operations, this dissertation optimizes vehicle loads and departure times from the terminal for each order of multi-temperature food, taking into account the fleet size decided during medium-term planning. Furthermore, this dissertation formulates mathematical models to estimate emissions from and Multi-Temperature Joint Delivery (MTJD) and Traditional Multi-Vehicle Delivery (TMVD) systems for food under time-dependent demand and various levels of traffic congestion. The emissions of the two systems are analyzed and compared under conditions of minimized delivery cost. Finally, the optimal vehicle load of a multi-temperature joint delivery system is analyzed with carbon tax. A series of numerical examples illustrate the application of the proposed model. The results suggest that carriers determine departure times of multi-temperature food with demand-supply interaction to increase profit. In addition, when shipping demand exceeds fleet capacity, the carrier should deliver food of medium temperature ranges with priority because delivering such food yields more profit. The results indicate that, as compared to the TMVD system, the MTJD system yields less total emissions by lowering fuel consumption even when it generates more CO2e due to refrigerant leakage and electric power consumption for freezers. This dissertation suggests carriers use the MTJD system to reduce routing distances and emissions simultaneously. The results show that in the MTJD system, there exists economies of scale in the relationship between carbon footprints and distributed volume. However, in the TMVD system, the influence of distributed volume on average carbon footprints is not noticeable. For the delivery scheduling under carbon tax, the results suggest carrier delivers the food with high density at periods with high road speed and transport the food with low density at periods with low road speed. Thus, the delivery and emissions cost can be reduced simultaneously. The results show that carbon tax does not raise carriers’ cost, even helps carrier reduce delivery cost because more influence related to energy consumption are taken into account.

In light of the demand for high-quality fresh food, transportation requirements for fresh food delivery have been continuously increasing in urban areas. Jointly delivering foods with different temperature-control requirements is an important issue for urban logistic carriers who transport both low temperature-controlled foods and normal merchandise. On the other hand, sources of greenhouse gas (GHG) emissions related to food transportation include energy consumption and refrigerant leakage. HFCs and PFCs generated by refrigerant leakage markedly increase global warming potential (GWP), and many governments around the world have developed futures markets for emission allowances or levied carbon taxes. Given this, how to deliver multi-temperature food considering GHG emissions has become an important issue for carriers. This dissertation aims to analyze and optimize medium-term planning and short-term operation for multi-temperature food transportation. Moreover, this dissertation explores greenhouse gas emissions from multi-temperature food delivery. For medium-term planning, this dissertation optimizes fleet size for carriers considering time-dependent multi-temperature food demand. For short-term operations, this dissertation optimizes vehicle loads and departure times from the terminal for each order of multi-temperature food, taking into account the fleet size decided during medium-term planning. Furthermore, this dissertation formulates mathematical models to estimate emissions from and Multi-Temperature Joint Delivery (MTJD) and Traditional Multi-Vehicle Delivery (TMVD) systems for food under time-dependent demand and various levels of traffic congestion. The emissions of the two systems are analyzed and compared under conditions of minimized delivery cost. Finally, the optimal vehicle load of a multi-temperature joint delivery system is analyzed with carbon tax. A series of numerical examples illustrate the application of the proposed model. The results suggest that carriers determine departure times of multi-temperature food with demand-supply interaction to increase profit. In addition, when shipping demand exceeds fleet capacity, the carrier should deliver food of medium temperature ranges with priority because delivering such food yields more profit. The results indicate that, as compared to the TMVD system, the MTJD system yields less total emissions by lowering fuel consumption even when it generates more CO2e due to refrigerant leakage and electric power consumption for freezers. This dissertation suggests carriers use the MTJD system to reduce routing distances and emissions simultaneously. The results show that in the MTJD system, there exists economies of scale in the relationship between carbon footprints and distributed volume. However, in the TMVD system, the influence of distributed volume on average carbon footprints is not noticeable. For the delivery scheduling under carbon tax, the results suggest carrier delivers the food with high density at periods with high road speed and transport the food with low density at periods with low road speed. Thus, the delivery and emissions cost can be reduced simultaneously. The results show that carbon tax does not raise carriers’ cost, even helps carrier reduce delivery cost because more influence related to energy consumption are taken into account.