An integrated ACO-AHP approach for resource management optimization

The most often used operator to aggregate criteria in decision making problems is the classical weighted sum model or weighted sum model. However, in many problems, the criteria considered interact and a substitute to the weighted sum model has to be adopted. Multi-criteria decision making (MCDM) problems involve the ranking of a finite set of alternatives in terms of a finite number of decision criteria. Usually such criteria may be in conflict with each other. A typical problem in MCDA is concerned with the task of ranking a finite number of decision alternatives, each of which is explicitly described in terms of different characteristics often called decision criteria or objectives. This research applies an integrated multi-criteria decision making approach to design an optimal UAV resource management. In this approach, the ant colony optimization (ACO) is used firstly to obtain optimal solutions satisfying some path planning criteria, then, fuzzy analytic hierarchy process (AHP) is formulated to select the best set of UAVs. Due to vagueness and uncertainty, fuzzy set theory based AHP is employed in the decision making judgments, because it can handle uncertainty easily. The proposed method can be extended to any sensor network resource management problem.