Environmental impact becomes an emerging problem since global warming has caused climate change issues, especially natural disasters in recent years. Based on International Energy Agency (IEA), the concentration of CO2 in 2015 was 399 parts per million by volume and was about 40% higher than in the mid-1800s. Since the transportation sector accounts for great responsibility for emissions, how to reduce CO2 emissions and keep the efficiency of transportation has become a more important issue. Dial-a-ride Problem (DARP) is a new form of mobility-on-demand public transportation, and the route and schedule of DARP are flexible to accommodate customer needs. This study aims at integrating the concept of eco-efficiency into DARP, and a bi-objective dial-a-ride problem with time-dependent costs is formulated. Two objectives, CO2 emissions and travel time, are explicitly considered. The formulation considers the perspective of eco-efficiency and fluctuation of travel time for the dial-a-ride problem. A revised branch-and-price solution algorithm with a large neighbor search (LNS) is adopted to solve the problem. In order to solve the two objectives simultaneously, this study applies the weighted sum with the normalization approach. Due to the difficulties of estimating emissions, a traffic simulation model is incorporated with the solution algorithm to provide emissions values. Several experiments based on a city network are conducted to evaluate objectives based on different factors, including traffic condition, time window, and maximum ride time. The results show that (1) weights for objectives need to be designed appropriately to reflect the preference; (2) the travel times and CO2 emissions reduce with respect to the increase of time window length; (3) The total travel time and CO2 emissions decrease with respect to the length of maximum ride time.
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