Projects

1. A Route Optimization Software Platform Development 

Primary Investigator

Foundation Grants for Rotamopt, Inc. - A logistics optimization startup

Background

We joined and successfully completed the BİGG program organized by ODTÜ TEKNOKENT, KWORKS - Koç University Entrepreneurship Research Center and Arçelik Garage Inovation Hub. We then received the TÜBİTAK 1512 BİGG Grant focused on Green Growth. I also received the KOSGEB R&D and Innovation Grant. We were participated the Mobility Acceleration Program 2022 organized by TOGG and Bilişim Vadisi-Technology Development Zone. We were chosen to be one of the 10 startups that present on the stage at DemoDay. We were selected to Microsoft for Startups Founders Hub.

Aims

This project aimed to develop a world-class route optimization and delivery management software that helps last-mile operations with a highly efficient, powerful, and state-of-the-art academia-based optimization engine. 

Product Features

Rotamopt was built by a world-class team of route optimization and software engineering talent. It used the latest optimization algorithms from academia. The optimization engine (API) based on the internationally award-winning Ph.D. dissertation of the founder and highly-cited reputable academic articles. It successfully considers many real-world constraints, including vehicle types, vehicle capacity, travel speeds, task size and volumetric, delivery windows, and service time. Companies could easily customize constraints and quickly solve their problems. We provided a seamless API integration process. Rotamopt's powerful, developer-friendly API and flexible modules could be easily embedded into any logistics management system.

Output

These two prestigious fundings are the foundation grants for Rotamopt, Inc. - A logistics optimization startup. Rotamopt was founded in the incubation center of ODTU TEKNOKENT which is Türkiye's leading science and technopark and a globally successfull inovation ecosystem. 

2. Home Healthcare Electric Vehicle Routing and Scheduling Problems

Primary Investigator

Background

The aging and growing population in the world, especially in developed countries, increases the demand for home health care which has lower cost and high efficiency than treatment at hospitals. However, the spread of home health care (HHC) services brings additional workload to health workers. This service includes a wide range of services to people with disabilities and older people. HHC providers assign staff (usually nurses) who provide service to patients and plan their working time. Routes of the staff and time to visit each demand node should be determined. The main difference between traditional Vehicle Routing Problem (VRP), which aims to determines minimum cost routes for a fleet of vehicles to meet the demands of customers in different locations, and the Electric VRP is the using of electric vehicles to meet customer demands and consideration of the charging needs of these vehicles.

Abstract

In this project, four different versions of the Home Healthcare Electric Vehicle Routing and Scheduling Problems have been studied. These are (i) fast charging feature, (ii) multi-period and fast charging feature, (iii) heterogeneous vehicle fleet and fast charging feature, and (iv) dialysis service and public charging stations feature. Each problem is formulated as a mixed integer linear programming model. Comprehensive test problems are generated by considering real-life data. With the developed mathematical models, exact solutions have been obtained for small-sized problem examples. Effective and innovative metaheuristic algorithms including various advanced procedures were developed as a solution method for large-size instances of each problem type. These algorithms based on the successful heuristics from the literature such as constructive heuristics, variable neighborhood search, adaptive large neighborhood search, and greedy randomized adaptive search procedure. Obtained results are evaluated and discussed according to various performance measures. In the extensive computational experiments, the effectiveness of the developed optimization methods have been successfully demonstrated.

Outputs

Articles

Theses

Presentations

3. The Airport Shuttle Service Scheduling Problem

Primary Investigator

Abstract

In this project, we introduce the airport shuttle service scheduling problem (ASSSP) as a new practical scheduling variant. The ASSSP involves managing a fleet of identical vehicles, each with a specific number of available seats, to provide transfers between the airport and the city center. Once a transfer is made in one direction, the vehicle can either make another transfer in the opposite direction based on passenger availability and schedules or return empty to begin a new transfer in the same direction. The vehicles can wait in either location until their next assignment. Passenger transfer windows, related to their flight times, and operational rules are crucial to ensure customer satisfaction. This service is profit-seeking and may involve rejecting some transfer requests. The main objective of the ASSSP is to prepare a daily schedule for available vehicles and assign passengers to maximize the total profit.

To tackle this problem, the project presents two mixed integer programming formulations and introduces two valid inequalities to enhance the solution's accuracy. Additionally, a hybrid metaheuristic, integrating multi-start, simulated annealing, and large neighborhood search, is developed for an efficient solution. Extensive computational experiments on real-life benchmark instances are conducted to assess the performance of the formulations and the hybrid metaheuristic. Moreover, the study investigates the impact of several problem parameters, such as vehicle capacity, transfer fee, transportation time, and allowable passenger waiting times, on the problem complexity and results. The obtained results demonstrate the successful introduction and resolution of the ASSSP, with the proposed solution method proving to be highly effective and successful.

Outputs

Articles

Presentations

4. Analysis of Vehicle Emission on Location-Routing Problem

Primary Investigator

Abstract

This project analyzed the combined impact of location and vehicle routing decisions on emissions in the context of road freight transport. The objective of the Vehicle Routing Problem was to find the most cost-effective routes that fulfill all customer needs, while the Facility Location Problem focused on opening and operating the most cost-efficient facilities. A novel problem was explored, considering environmental objectives and time windows, known as the Location and Vehicle Routing Problem with environmental considerations.

The main goal of this problem was to minimize total costs associated with storage, drivers, fuel, and emissions. The project achieved the following objectives:

Overall, this project shed light on the intricate relationship between location and vehicle routing decisions and their influence on emissions in road freight transport, while offering valuable insights and practical solutions for addressing environmental objectives.

Outputs

Articles

Presentations