Multiobjective aerial surveillance over disjoint rectangles

Karasakal O., KARASAKAL E., Maraş G.

Computers and Industrial Engineering, vol.148, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 148
  • Publication Date: 2020
  • Doi Number: 10.1016/j.cie.2020.106732
  • Journal Name: Computers and Industrial Engineering
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Keywords: Travelling salesman, Aerial surveillance, Multiple objective programming, Unmanned aerial vehicles, ORIENTEERING PROBLEM, SEARCH
  • Middle East Technical University Affiliated: Yes


In Aerial Surveillance Problem (ASP), an air platform with surveillance sensors searches a number of rectangular areas by covering the rectangles in strips and turns back to base where it starts. In this paper, we present a multiobjective extension to ASP, for which the aim is to help aerial mission planner to reach his/her most preferred solution among the set of efficient alternatives. We consider two conflicting objectives that are minimizing distance travelled and maximizing minimum probability of target detection. Each objective can be used to solve single objective ASPs. However, from mission planner's perspective, there is a need for simultaneously optimizing both objectives. To enable mission planner reaching his/her most desirable solution under conflicting objectives, we propose exact and heuristic methods for multiobjective ASP (MASP). We also develop an interactive procedure to help mission planner choose the most satisfying solution among all Pareto optimal solutions. Computational results show that the proposed methods enable mission planner to capture the tradeoffs between the conflicting objectives for large number of alternative solutions and to eliminate the undesirable solutions in small number of iterations.