Fuzzy Mixed Integer Linear Programming for Air Vehicles Operations Optimization
This addresses a domain-specific optimization problem for military operations like those in the Indian Air Force, providing an incremental improvement by applying FMILP to task scheduling.
The authors tackled the problem of optimally scheduling multiple air vehicles to perform classification, attack, and verification tasks on dispersed targets with time constraints, by formulating it as a Fuzzy Mixed Integer Linear Programming (FMILP) problem, which assigns tasks and schedules departures to minimize time while guaranteeing an optimal solution when vehicles have sufficient endurance.
Multiple Air Vehicles (AVs) to prosecute geographically dispersed targets is an important optimization problem. Associated multiple tasks viz., target classification, attack and verification are successively performed on each target. The optimal minimum time performance of these tasks requires cooperation among vehicles such that critical time constraints are satisfied i.e. target must be classified before it can be attacked and AV is sent to target area to verify its destruction after target has been attacked. Here, optimal task scheduling problem from Indian Air Force is formulated as Fuzzy Mixed Integer Linear Programming (FMILP) problem. The solution assigns all tasks to vehicles and performs scheduling in an optimal manner including scheduled staged departure times. Coupled tasks involving time and task order constraints are addressed. When AVs have sufficient endurance, existence of optimal solution is guaranteed. The solution developed can serve as an effective heuristic for different categories of AV optimization problems.