Integration of DEA and AHP with computer simulation for railway system improvement and optimization

Abstract: This paper presents an integrated simulation, multivariate analysis and multiple decision analysis for railway system improvement and optimization. Furthermore, the integrated model is based on data envelopment analysis (DEA) and analytical hierarchy process (AHP) that is integrated with computer simulation . The integrated DEA and AHP simulation model can be used for selecting optimum alternatives by considering multiple quantitative and qualitative inputs and outputs. First, computer simulation is used to model verify and validate the system being studied. Second, AHP methodology determines the weight of any qualitative criteria (input or outputs). Finally, the DEA model is used to solve the multi-objective model to identify the best alternative(s) and also to identify the mechanism to optimize current system. An 800-km train route system was selected as the case of this study. Visual SLAM language was used to develop the simulation model of the railway system. The objective of simulation model is to increase reliability related to the time table of the passenger trains, to decrease average traverse time of passenger trains and to decrease average traverse time of cargo trains. In addition, for multivariate assessment of the alternatives by DEA, safety and cost factors are derived and considered from an AHP analysis. Previous studies use simulation and DEA based on quantitative variables for identification of the most efficient scenarios, while this study considers both quantitative and qualitative variables for efficiency assessment and performance optimization by integration of simulation, DEA and AHP. This is quite important for systems where some of their performance measures are qualitative such as railway and production systems. [Copyright &y& Elsevier]