Mathematical Optimization in Innovation Productivity: A Framework and A Case Study on UAV Border Patrolling in Türkiye

Year 2024, Volume: 58 Issue: 2, 283 - 304, 30.04.2024

Erdi Daşdemir

https://doi.org/10.51551/verimlilik.1322882

Abstract

Purpose: In this paper, the potential of mathematical optimization (MO) in enhancing innovation productivity is explored. Innovation is a process that converts new ideas and methods into products and services, MO can contribute to innovation management by improving productivity across all stages, from pre-innovation to post-innovation. This paper establishes a connection between MO and innovation productivity while demonstrating an application for a post-innovation phase problem of unmanned aerial vehicles (UAVs).
Methodology: A framework for incorporating MO into the design problems of innovation processes is developed. Additionally, a MO model is developed for a case study concerning UAV border patrolling in Türkiye.
Findings: Computational experiments demonstrate MO's effectiveness in optimizing UAV routes and strategies, enhancing operational efficiency, and innovation productivity. Optimal recommendations and trade-offs among different mission considerations are obtained in 18 minutes on average (with a median of 5 seconds) over 210 runs.
Originality: A link is established between MO and innovation productivity. An operations research problem is introduced for UAV operations in border patrolling in Türkiye. The codebase and data are openly provided for readers to apply the model in their research.

Keywords

Mathematical Optimization, Innovation, Productivity, Unmanned Aerial Vehicles

İnovasyon Verimliliğinde Matematiksel Optimizasyon: Bir Çerçeve ve Türkiye’de İHA Sınır Devriyesine İlişkin Bir Vaka Çalışması

Abstract

Amaç: Bu makalede, matematiksel optimizasyonun (MO) inovasyon verimliliğini artırma potansiyeli incelenmektedir. İnavasyon, yeni fikirleri ve yöntemleri ürün ve hizmetlere dönüştüren bir süreçtir. MO, inovasyon yönetimine verimliliği artırarak katkıda bulunabilir; bu, inovasyon öncesinden sonrasına kadar inovasyon sürecinin tüm aşamalarında geçerlidir. Bu makale, MO ve inovasyon verimliliği arasında bir bağlantı kurarken, insansız hava araçlarının (İHA'ların) inovasyon sonrası aşamasındaki problemlerine yönelik bir uygulama sunmaktadır.
Yöntem: İnovasyon süreçlerindeki karar problemlerine MO'nun dahil edilişi için bir çerçeve oluşturulmaktadır. Ayrıca, Türkiye'deki İHA sınır devriyesi ile ilgili bir vaka çalışması için bir MO modeli geliştirilmektedir.
Bulgular: Hesaplamalı deneyler, MO'nun İHA rotalarını ve stratejilerini optimize etme, operasyonel verimliliği ve inovasyon verimliliğini artırma konusundaki etkinliğini göstermektedir. Model, optimal tavsiyeleri ve farklı endişeler için dengeleri 210 farklı çözüm için ortalama 18 dakikada (medyan 5) bulmaktadır.
Özgünlük: MO ve inovasyon verimliliği arasında bir bağlantı kurulmuştur. Türkiye'de sınır devriyesi için İHA operasyonları için bir yöneylem araştırması problemi sunulmaktadır. Okuyucuların araştırmalarında modeli uygulayabilmeleri için kod tabanı ve veriler açık sunulmaktadır.

Keywords

Matematiksel Optimizasyon, İnovasyon, Verimlilik, İnsansız Hava Araçları.

Thanks

Buffalo Üniversitesi'ne, Hesaplama Araştırmaları Merkezi'nin yüksek performanslı bilgisayar kaynaklarında deneylerimizi gerçekleştirmeme izin verdiği için teşekkür ederim.

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