A genetic algorithm for solving bus terminal location problem using data envelopment analysis with multi-objective programming

Abstract

Due to urbon expansion and population increasing bus network design is an important problem in public transportation. Functional aspect of bus networks such as fuel consumption and the depreciation of buses and also spatial aspects of bus networks such as station and terminal locations or access rate to the buses are not proper conditions in most cities. Therefore, having an efficient method to evaluate the performance of bus lines considering both functional and spatial aspects is essential. In this paper, we propose a new model for bus terminal location problem (BTLP) using data envelopment analysis (DEA) with multi-objective programming approach. In this model, we want to find an efficient allocation patterns for assigning stations terminals and also we find the optimal locations for deploying terminals. So we use genetic algorithm for solving our model. By simultaneous combing the data envelopment analysis and bus terminal location problem, two types of

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