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

Author:

Daşdemir Erdi1ORCID

Affiliation:

1. HACETTEPE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, ENDÜSTRİ MÜHENDİSLİĞİ BÖLÜMÜ, ENDÜSTRİ MÜHENDİSLİĞİ ANABİLİM DALI

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.

Publisher

Stratejik Arastirmalar ve Verimlilik Genel Mudurlugu Verimlilik Dergisi

Reference42 articles.

1. Ackoff, R.L. (1979). "The Future of Operational Research is Past", The Journal of the Operational Research Society, 30(2), 93-104.

2. Arf, C. (1959). "Makine Düşünebilir Mi ve Nasıl Düşünebilir?", Atatürk Üniversitesi – Üniversite Çalışmalarını Muhite Yayma ve Halk Eğitimi Yayınları Konferanslar Serisi, 1, 91-103.

3. Baykar (2023). "Bayraktar Akinci" https://baykartech.com/tr/uav/bayraktar-akinci/ (Access date: 29.03.2024).

4. Braekers, K., Ramaekers, K. and Van Nieuwenhuyse, I. (2016). "The Vehicle Routing Problem: State of the Art Classification and Review", Computers & Industrial Engineering, 99, 300-313.

5. Camm, J.D., Cochran, J.J., Fry, M.J. and Ohlmann, J.W. (2020). "Business Analytics", Cengage Learning, Boston.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3