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Journals / Endüstri Mühendisliği / 2026 / Cilt: 37 Sayı: 2

A METAHEURISTIC-BASED APPROACH FOR DYNAMIC ROUTE OPTIMIZATION OF AUTONOMOUS ELECTRIC VEHICLES

OTONOM ELEKTRİKLİ ARAÇLAR İÇİN DİNAMİK ROTA OPTİMİZASYONUNDA METASEZGİSEL TABANLI BİR YÖNTEM

Taha Akkurt(ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ)0000-0002-0821-9854
İnci Sarıçiçek(ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ, AKILLI SİSTEMLER UYGULAMA VE ARAŞTIRMA MERKEZİ)0000-0002-3528-7342
Ahmet Yazici(ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ, AKILLI SİSTEMLER UYGULAMA VE ARAŞTIRMA MERKEZİ)0000-0001-5589-2032
Pages
381–411
Publication Date
2026-08-28
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Consequently, the developed metaheuristic-based method provides a flexible, scalable, and effective solution alternative for multi-vehicle autonomous electric vehicle routing problems that are sensitive to real-time dynamics.

📌 3 Key Takeaways

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Objective & Hypothesis:The use of autonomous electric vehicles in transportation systems is rapidly increasing due to their zero-emission characteristics and real-time decision-making capabilities.
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Key Findings & Data:However, limitations such as restricted battery capacity, time-consuming charging processes, and insufficient charging infrastructure hinder the direct application of classical vehicle routing approaches and increase the need for dynamic and constraint-aware solution methods.
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Conclusion & Impact:Consequently, the developed metaheuristic-based method provides a flexible, scalable, and effective solution alternative for multi-vehicle autonomous electric vehicle routing problems that are sensitive to real-time dynamics.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Dinamik Araç Rotalama · Otonom Elektrikli Araçlar · Yasaklı Arama

Abstract

The use of autonomous electric vehicles in transportation systems is rapidly increasing due to their zero-emission characteristics and real-time decision-making capabilities. However, limitations such as restricted battery capacity, time-consuming charging processes, and insufficient charging infrastructure hinder the direct application of classical vehicle routing approaches and increase the need for dynamic and constraint-aware solution methods. In this study, a dynamic route planning approach capable of adapting to real-time conditions for autonomous electric vehicles is proposed. Within a depot-based distribution framework, the initial route for each vehicle is generated using the Tabu Search (TS) metaheuristic. Throughout the routing process, vehicle battery levels are continuously monitored, and vehicles are directed to the most appropriate charging stations when energy constraints become critical. Charging durations and time window violations are incorporated into the total cost function to enhance the operational feasibility of the solution. The proposed approach is designed to adapt in real time to unexpected events in dynamic environments, such as newly arriving customer requests, order cancellations, variations in traffic congestion, and road closures or reopenings. This adaptive structure enables the system to maintain service continuity while keeping total operational costs under control. Consequently, the developed metaheuristic-based method provides a flexible, scalable, and effective solution alternative for multi-vehicle autonomous electric vehicle routing problems that are sensitive to real-time dynamics.

Özet

Otonom elektrikli araçların, sıfır emisyonlu yapıları ve gerçek zamanlı karar verme yetenekleri sayesinde taşımacılık sistemlerindeki kullanımı hızla artmaktadır. Bununla birlikte, batarya kapasitesinin sınırlı olması, şarj süreçlerinin zaman alıcı yapısı ve şarj altyapısındaki yetersizlikler, klasik araç rotalama yaklaşımlarının doğrudan uygulanmasını güçleştirmekte, dinamik ve kısıt duyarlı çözüm yöntemlerine olan ihtiyacı artırmaktadır. Bu çalışmada, otonom elektrikli araçlar için gerçek zamanlı koşullara uyum sağlayabilen dinamik bir rota planlama yaklaşımı önerilmektedir. Depo merkezli dağıtım yapısı altında, her bir aracın başlangıç rotası Yasaklı Arama (TS) metasezgisel yöntemi kullanılarak oluşturulmuştur. Rotalama süreci boyunca araçların batarya seviyeleri sürekli olarak izlenmiş ve enerji yetersizliği durumunda araçlar en uygun şarj istasyonlarına yönlendirilmiştir. Şarj süreleri ile zaman penceresi ihlalleri, toplam maliyet fonksiyonuna entegre edilerek çözümün operasyonel açıdan uygulanabilirliği artırılmıştır. Önerilen yaklaşım, dinamik ortamlarda ortaya çıkan yeni müşteri talepleri, talep iptalleri, trafik yoğunluğundaki değişimler ve yol kapanma veya açılma gibi beklenmedik durumlara gerçek zamanlı olarak uyum sağlayacak biçimde tasarlanmıştır. Bu adaptif yapı sayesinde sistem, hizmet sürekliliğini korurken toplam operasyonel maliyetin kontrol altında tutulmasını mümkün kılmaktadır. Sonuç olarak geliştirilen metasezgisel tabanlı yöntem, çoklu araçlı ve gerçek zamanlı değişkenlere duyarlı otonom elektrikli araç rotalama problemleri için esnek, ölçeklenebilir ve etkili bir çözüm alternatifi sunmaktadır.

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Cite This Article

Akkurt, T., Sarıçiçek, İ., Yazici, A. (2026). A METAHEURISTIC-BASED APPROACH FOR DYNAMIC ROUTE OPTIMIZATION OF AUTONOMOUS ELECTRIC VEHICLES. Endüstri Mühendisliği, Cilt: 37 Sayı: 2, 381–411. https://doi.org/10.46465/endustrimuhendisligi.1861062

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