E. Loureiro, N. Figueiredo, Lúcio Carlos Pinheiro Campos Filho, T. Filgueiras
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引用次数: 1
摘要
水路运输对亚马逊地区的人口至关重要。根据Agência national de Transportes Aquaviários (Antaq, 2018)的数据,它负责通过州际、州际和跨州纵向运输运输约980万名乘客和340万吨货物。然而,尽管非常重要,但在某些路线上仍有一些与道路和船只状况有关的堵塞。该研究提出使用数学工具从涉及输入和输出参数的相对效率来分析船舶,分为两种分析情景:能效分析和模态分析,被分析的变量包括功率、消耗、行程总时间、行动线总距离、载客量和票价。为此,我们对652艘在亚马逊地区注册的巴西各州(par、Amazonas、amap和Rondônia)的船舶数据进行了验证,并从这些数据中选择了148艘相同利用水平的船舶样本空间。根据这些数据,在DEA- solver软件的帮助下,使用数据包络分析(DEA)方法开发了一个模型。使用求解器后,得到各船的相对效率指标,从而对有效和无效决策单元(DMU’s)进行排序和测量。最后,对高效船舶的一般特征进行了分析,以便对可能将其转化为高效DMU的参数进行分层,从而有可能跟踪每种类型航线所使用的船舶类型的概况,从而有助于新项目的决策。
Analysis of relative efficiency of vessels of passenger transportation in the Brazilian Amazon: an AHP-DEA approach
Waterway transport is of great importance for the population of the Amazon Region. It is responsible for moving, according to Agência Nacional de Transportes Aquaviários (Antaq, 2018), approximately 9.8 million passengers and 3.4 million tons of cargo distributed by state, interstate longitudinal transport interstate and crossing. However, despite the great importance, there are several blockages related to the conditions of the roads and vessels in certain routes. The study in question proposes the use of a mathematical tool to analyze vessels from the relative efficiency involving parameters of input and output for two analysis scenarios: Energy Efficiency Analysis and Modality Analysis, being analyzed variables such as power, consumption, total time of the trip, total distance of the line of action, passenger capacity and ticket price. For that, the data of 652 vessels used in the Amazon region registered in the Brazilian states (Pará, Amazonas, Amapá and Rondônia) were verified, and from these data, a sample space of 148 vessels from the same utilization level was selected. With these data, a model was developed using the Data Envelopment Analysis (DEA) methodology, with the aid of the DEA-Solver software. After the use of the solver, the relative efficiency indexes of each vessel were obtained, allowing to rank and measure the efficient and inefficient Decision Units (DMU'S). Lastly, analysis of the general characteristics of efficient vessels were made in order to stratify the parameters that may have transformed them into efficient DMU`s, making it possible to trace a profile of the type of vessel employed in each type of line, thus helping in decision making of new projects.
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