Fuzzy Mixed Integer Linear Programming for Air Vehicles Operations Optimization

TL;DR

This paper formulates an optimal scheduling problem for multiple air vehicles performing target classification, attack, and verification tasks using Fuzzy Mixed Integer Linear Programming, ensuring cooperation and time constraints are met.

Contribution

It introduces a novel FMILP model for air vehicle task scheduling, addressing coupled tasks and staged departure times for optimal performance.

Findings

Optimal solutions guaranteed with sufficient AV endurance

The FMILP model effectively schedules tasks with time and order constraints

Proposed solution can serve as a heuristic for various AV optimization problems

Abstract

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.