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From airplanes to electric vehicles and trains, modern transportation systems require large quantities of energy. These vast amounts of energy have to be produced somewhere—ideally by using sustainable sources—and then brought to the transportation system. Energy is a scarce and costly resource, which cannot always be produced from renewable sources. Therefore, it is critical to consume energy as efficiently as possible, that is, transportation activities need to be carried out with an optimal intake of energetic means. This paper reviews existing work on the optimization of energy consumption in the area of transportation, including road freight, passenger rail, maritime, and air transportation modes. The paper also analyzes how optimization methods—of both exact and approximate nature—have been used to deal with these energy-optimization problems. Finally, it provides insights and discusses open research opportunities regarding the use of new intelligent algorithms—combining metaheuristics with simulation and machine learning—to improve the efficiency of energy consumption in transportation.

The estimation of the noise impact caused by road freight transportation is critical to have acknowledgment of the ambiance pollution caused by road traffic crossing geographical areas containing important natural resources. Thus, our work proposes a within-subject survey where a Contingent Valuation Method (CVM) is combined with a laboratory economic experimental auction. Our study objective is to measure the willingness-to-pay (WTP) for reducing traffic noise nuisances due to freight transportation in the region of Navarre, Spain. A special focus is made regarding the measurement of the hypothetical bias, when a comparison is done between hypothetical WTP, coming from the CVM study, with real-incentivized one, as the outcome of the economic experiment. Additionally, statistical analyses are conducted in order to find explanation factors for these outcomes. Results suggest a strong evidence for an upward hypothetical bias (from 50% to 160%) indicating the income, the educational level, the gender, and the age as the main factors which explain that bias.

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Biofuels are emerging as a prominent renewable and sustainable energy sources in developed countries. In this sense, this paper presents a case study in which a biorefinery has to be sited is investigated in Northern Spain. Thus, the strategic decision of locating such a facility is deeply investigated through strategic policy evaluation. Then, tactical decisions ranging from purchase policy, transport policy and storage policy are carried out. Only local and limited biomass can be harvested for supplying the biorefinery through a heterogeneous vehicle fleet and two different and mutually exclusive storage strategies are evaluated: direct supply from crops to biorefinery and using intermediate-collectors. Additionally, crop exploitation factors and biorefinery sizes are used to generate several scenarios in which the strategic decision of location as well as all the tactic decisions are made. Some mixed integer linear programming models are proposed to figure out all relevant decision problems. The results suggest that the northwest study area as the best option to locate the biorefinery and recommend the intermediate-collector storage strategy. Moreover, key information about critical biomass, crops and times are also provided.

We designed a survey that aims at estimating individual willingness-to-pay to reduce noise and air pollution arising from transportation activity near the Pyrenees in Navarre (Spain). Our participants cope with a series of contingent valuation questions and also with an economic experiment with real incentives about the same topic. Our goal is to identify several methodological problems in the valuation process coming from hypothetical bias, correlation effect and sequence effect when series of responses are requested. Our main results are that hypothetical bias is significant, because the willingness-to-pay is greater when the survey is hypothetical compared to when there is real monetary incentive. Likewise, the correlation effect also observes the same behaviour since the willingness-to-pay for pollution mitigation is close to the one established for noise reduction. Finally, we have obtained mixed evidence for the sequence effect, being present only in the contingent valuation survey part.

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