Integer Linear Programming Approach for the Personnel Shuttles Routing Problem in Yıldız Campus in Istanbul




Vehicle routing problem, Personnel shuttle routing problem, School bus routing problem, Integer linear programming, Decision analytics


The Vehicle Routing Problem (VRP) revolves around the challenge of determining optimal vehicle routes for a company to efficiently serve a specific number of customers while minimizing costs. The Personnel Shuttle Routing Problem (PSRP) is a specialized variation of the VRP which focuses on optimizing shuttle or transportation services for individuals or small groups in specific contexts like universities, institutions or corporate campuses. The PSRP is of interest mostly in developed countries as it can lead to improved transportation efficiency, reduced environmental impact, and enhanced passenger satisfaction. This article details an optimization study conducted to address the PSRP within Yildiz Technical University’s Yildiz campus in 2021. The primary objective is to identify routes that minimize travel distances while ensuring balanced service coverage, all while adhering to specific constraints. The optimization approach leverages Integer Linear Programming to formulate a mathematical decision model. Data and information pertinent to the problem were acquired through consultations with the Yildiz Technical University General Secretary Support Unit managers. The resulting decision model was implemented using the GAMS 34.3.0 software package as a decision analytic programme, and the problem was solved by splitting it into two parts, addressing the Anatolian and European sides of the campus separately. The study culminated in a notable achievement: a reduction of 10.88% in the travel distances associated with Yildiz campus personnel shuttle routes.


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How to Cite

Tütüncü, K. A., Gül, N. N., Bölükbaş, U., & Güneri, A. F. (2023). Integer Linear Programming Approach for the Personnel Shuttles Routing Problem in Yıldız Campus in Istanbul. Journal of Soft Computing and Decision Analytics, 1(1), 303-316.