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

Atefeh Taghavi, Reza Ghanbari, Khatere Ghorbani-moghadam, Alireza Davoodi*, Ali Emrouznejad

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Due to the urban expansion and population increasing, bus network design is an important problem in the public transportation. Functional aspect of bus networks such as the fuel consumption and 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 by considering both functional and spatial aspects is essential. In this paper, we propose a new model for the bus terminal location problem using data envelopment analysis with multi-objective programming approach. In this model, we want to find efficient allocation patterns for assigning stations terminals, and also we investigate the optimal locations for deploying terminals. Hence, we use a genetic algorithm for solving our model. By using the simultaneous combination of data envelopment analysis and bus terminal location problem, two types of efficiencies are optimized: Spatial efficiency as measured by finding allocation patterns with the most serving amount and the terminals’ efficiency in serving demands as measured by the data envelopment analysis efficiency score for selected allocation patterns. This approach is useful when terminals’ efficiency is one of the important criteria in choosing the optimal terminals location for decision-makers.
Original languageEnglish
JournalAnnals of Operations Research
Early online date29 Aug 2021
DOIs
Publication statusE-pub ahead of print - 29 Aug 2021

Bibliographical note

© Springer Nature B.V. 2021. The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-021-04244-4.

Funding: The authors thank the research council of Ferdowsi University of Mashhad and Optimization Laboratory of Ferdowsi University of Mashhad for supporting this work.

Keywords

  • Bus terminal location problem
  • Data envelopment analysis
  • Efficiency
  • Genetic algorithm
  • Multi objective programming

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