MS Student Position

Funding: TÜBİTAK 1001

Project Title: Dual-Visit Service Logistics with Time-Dependent Travel Times

Position Duration: 2 years

Project Overview

Transportation planning for service sector employees is a highly valuable area that has been widely studied in the literature (Castillo-Salazar et al., 2016). Whether in on-site healthcare services (Di Mascolo et al., 2021) or in social services (Batlle et al., 2022), efficient transportation planning plays a critical role in ensuring employee comfort, reducing costs, preventing disruptions in workflows, and avoiding public inconvenience.

This project addresses the novel Dual-Visit Service Logistics Problem with Time-Dependent Travel Times, combining within a single optimization framework three routing problem dimensions that have typically been studied in isolation: (i) selectivity, (ii) mandatory dual visits, and (iii) time-dependent travel times (Vansteenwegen et al., 2011; Adamo et al., 2024). As examples of dual-visit requirements with time-dependent travel times, one may cite the transportation of home healthcare personnel and the field travel of social service workers (Kodwo-Nyameaze et al., 2024; Atta et al., 2025).

The aim is to develop software that will optimize and manage route and service selections while accounting for time-dependent travel times — a challenge that is especially pronounced in traffic-congested metropolises such as Istanbul — thereby reducing operational costs, improving service quality, and supporting sustainability goals.

Within the scope of the project, two optimization approaches will be developed and their performance will be evaluated on synthetic datasets inspired by real-world problem sizes. An adaptive hybrid modeling pipeline will be explored, in which one model can feed the other (or itself with updated parameters). Based on the analyses and depending on the scale of the problem, the pipeline will determine the most effective optimization model, the appropriate parameter set, and the best direction of flow.

Responsibilities

As an MS student, you are expected to perform mathematical modeling, implement the code for the SVRP model, and help us develop a web-based system within the project.

Application

Interviews will be conducted on a rolling basis.

Contact: erhun.kundakcioglu@sabanciuniv.edu

Please use [MS APPLICATION] as your email subject and include the following in your application:

• Cover letter describing your research background, interests, and how they align with the project requirements
• CV
• Transcript