SYNERGIZING GEOGRAPHIC INFORMATION SYSTEMS (GIS) AND MULTICRITERIA DECISION MAKING ANALYSIS (MCDA) FOR PUBLIC TRANSIT NETWORK OPTIMIZATION: A REVIEW

Barham Salah Nsaif; Nihad Davut Hassan; Qais F Hasan

Authors

Barham Salah Nsaif Technical Engineering College, Northern Technical University, Kirkuk, Iraq
Nihad Davut Hassan Technical Engineering College, Northern Technical University, Kirkuk, Iraq
Qais F Hasan Technical Engineering College, Northern Technical University, Kirkuk, Iraq

Keywords:

Geographic Information Systems (GIS), Multi-Criteria Decision-Making (MCDA), Analytical Hierarchy Process (AHP), Public Bus Transport, Route Optimization, Spatial Analysis.

Abstract

This paper provides a detailed overview of the integration of Geographic Information Systems (GIS) and Analytical Hierarchy Process (AHP) approaches in the optimization of public bus transport networks. The review includes a comprehensive analysis of the literature as well as a discussion of the major findings, computing effectiveness, utility, and possible directions for future research. Because it smoothly blends multi-criteria decision-making and spatial analysis, the combination of GIS and AHP shows to be a useful tool in handling the complexities inherent in public transportation planning. The study investigates the use of GIS in integrating optimization models, expressing network data, performing geographical and temporal analysis, and assisting in decision-making. It looks at studies that have utilized GIS to optimize routes in an efficient manner, showcasing the many approaches and methods that have been used in the literature. The report also identifies the primary findings and constraints of GIS and AHP integration research. The benefits of using GIS-AHP models in decision support systems for companies involved in urban planning and transportation are highlighted in the discussion. The study concludes with a prospective exploration of possible directions for future research, including the addition of new data sources, flexible demand modeling, and state-of-the-art optimization techniques.

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