چكيده به لاتين
Abstract:
Studies show that by 2030 , trips within the city from about twelve million will reach to 19 million including satellite cities and in a 25 year period will increase by about 60%. Following to this increase, the share of rail transport will also increase; that this requires the development of railway network. According to the strategic plan of mass rail and civil express transportation in Tehran and Suburbs in 2030, the total length of Metro lines will reach 430 km that will results to increase of demand and consequently related rail fleet equipments. Therefore, the issue of selection of suppliers in this area will become more important; because any mistake in decision-making in this area will result in huge losses of national capitals. In the selection of suppliers we have to analyze and measure the performance of suppliers to rank them and then, allocate orders to them. On the other hand, in many cases in real issues, we are facing with different and sometimes conflicting criteria that should be simultaneously applied in the analyses. Therefore this sort of problems can be categorized in multi-criteria decision making issues. The aim of this study is to develop a multi-criteria - multi-objective hybrid model to prioritize and allocate orders to suppliers of railway fleet equipment. For this purpose, first the important criteria were determined through a review of the related literature and after identifying the alternatives, the problem was solved by applying an AHP model. At the end of the first phase, the outputs of the problem that are the weights of each of alternatives were used as inputs of the next phase of model that is the issue of multi-objective functions. In this phase, a multi-objective model was developed by using the coefficients obtained from the previous stage. In the final stage after coding the model at Lingo software and solve it, the amount of supply for each supplier were allocated for future procurement panning of equipments.
Keywords: Rail fleet equipment, Prioritization and allocation of orders, AHP, Multi-objective decision making.