Dealing with Multiple Optimization Objectives for UAV Path Planning in Hostile Environments: A Literature Review
As Unmanned Aerial Vehicles (UAVs) are becoming crucial in modern warfare, research on autonomous path planning is becoming increasingly important. The conflicting nature of the optimization objectives characterizes path planning as a multi-objective optimization problem. Current research has predom...
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MDPI AG
2024-12-01
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| Series: | Drones |
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| author | Thomas Quadt Roy Lindelauf Mark Voskuijl Herman Monsuur Boris Čule |
| author_facet | Thomas Quadt Roy Lindelauf Mark Voskuijl Herman Monsuur Boris Čule |
| author_sort | Thomas Quadt |
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| description | As Unmanned Aerial Vehicles (UAVs) are becoming crucial in modern warfare, research on autonomous path planning is becoming increasingly important. The conflicting nature of the optimization objectives characterizes path planning as a multi-objective optimization problem. Current research has predominantly focused on developing new optimization algorithms. Although being able to find the mathematical optimum is important, one also needs to ensure this optimum aligns with the decision-maker’s (DM’s) most preferred solution (MPS). In particular, to align these, one needs to handle the DM’s preferences on the relative importance of each optimization objective. This paper provides a comprehensive overview of all preference handling techniques employed in the military UAV path planning literature over the last two decades. It shows that most of the literature handles preferences by the overly simplistic method of scalarization via weighted sum. Additionally, the current literature neglects to evaluate the performance (e.g., cognitive validity and modeling accuracy) of the chosen preference handling technique. To aid future researchers handle preferences, we discuss each employed preference handling technique, their implications, advantages, and disadvantages in detail. Finally, we identify several directions for future research, mainly related to aligning the mathematical optimum to the MPS. |
| format | Article |
| id | doaj-art-0e17077df2f64e56bed8454bede181d6 |
| institution | DOAJ |
| issn | 2504-446X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-0e17077df2f64e56bed8454bede181d62025-08-20T02:55:41ZengMDPI AGDrones2504-446X2024-12-0181276910.3390/drones8120769Dealing with Multiple Optimization Objectives for UAV Path Planning in Hostile Environments: A Literature ReviewThomas Quadt0Roy Lindelauf1Mark Voskuijl2Herman Monsuur3Boris Čule4Department of Cognitive Science and AI, Tilburg School of Humanities and Digital Sciences, Tilburg University, P.O. Box 90153 Tilburg, The NetherlandsDepartment of Cognitive Science and AI, Tilburg School of Humanities and Digital Sciences, Tilburg University, P.O. Box 90153 Tilburg, The NetherlandsData Science Centre of Excellence, Faculty of Military Sciences, Netherlands Defence Academy, P.O. Box 20701 Hague, The NetherlandsData Science Centre of Excellence, Faculty of Military Sciences, Netherlands Defence Academy, P.O. Box 20701 Hague, The NetherlandsDepartment of Cognitive Science and AI, Tilburg School of Humanities and Digital Sciences, Tilburg University, P.O. Box 90153 Tilburg, The NetherlandsAs Unmanned Aerial Vehicles (UAVs) are becoming crucial in modern warfare, research on autonomous path planning is becoming increasingly important. The conflicting nature of the optimization objectives characterizes path planning as a multi-objective optimization problem. Current research has predominantly focused on developing new optimization algorithms. Although being able to find the mathematical optimum is important, one also needs to ensure this optimum aligns with the decision-maker’s (DM’s) most preferred solution (MPS). In particular, to align these, one needs to handle the DM’s preferences on the relative importance of each optimization objective. This paper provides a comprehensive overview of all preference handling techniques employed in the military UAV path planning literature over the last two decades. It shows that most of the literature handles preferences by the overly simplistic method of scalarization via weighted sum. Additionally, the current literature neglects to evaluate the performance (e.g., cognitive validity and modeling accuracy) of the chosen preference handling technique. To aid future researchers handle preferences, we discuss each employed preference handling technique, their implications, advantages, and disadvantages in detail. Finally, we identify several directions for future research, mainly related to aligning the mathematical optimum to the MPS.https://www.mdpi.com/2504-446X/8/12/769UAVpreference handlingmulti-objective optimizationpath planningradarmission planning |
| spellingShingle | Thomas Quadt Roy Lindelauf Mark Voskuijl Herman Monsuur Boris Čule Dealing with Multiple Optimization Objectives for UAV Path Planning in Hostile Environments: A Literature Review Drones UAV preference handling multi-objective optimization path planning radar mission planning |
| title | Dealing with Multiple Optimization Objectives for UAV Path Planning in Hostile Environments: A Literature Review |
| title_full | Dealing with Multiple Optimization Objectives for UAV Path Planning in Hostile Environments: A Literature Review |
| title_fullStr | Dealing with Multiple Optimization Objectives for UAV Path Planning in Hostile Environments: A Literature Review |
| title_full_unstemmed | Dealing with Multiple Optimization Objectives for UAV Path Planning in Hostile Environments: A Literature Review |
| title_short | Dealing with Multiple Optimization Objectives for UAV Path Planning in Hostile Environments: A Literature Review |
| title_sort | dealing with multiple optimization objectives for uav path planning in hostile environments a literature review |
| topic | UAV preference handling multi-objective optimization path planning radar mission planning |
| url | https://www.mdpi.com/2504-446X/8/12/769 |
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