Presenting the Multi-Objective Optimization Model of Search and Rescue Network

TL;DR

This paper develops a multi-objective optimization model for efficiently assigning HFDF receivers in Search and Rescue networks, balancing coverage and fairness, demonstrated through MATLAB simulations.

Contribution

It introduces a novel multi-objective optimization model for HFDF receiver assignment in SAR networks, independent of transmitter area weights.

Findings

The model effectively maximizes expected LOB coverage.

It ensures fair distribution of HFDF receivers across frequency areas.

MATLAB CPLEX successfully solves the optimization problem.

Abstract

The Search and Rescue Network (SAR) is a kind of emergency network that pursuit people in need or imminent danger. This paper aims using a priori optimization to demonstrate the optimal assignment of HFDF receivers to the Generalized Search and Rescue (GSAR) network, which is independent of the weighting of the transmitter areas. The mathematical model seeks two objectives, the first one is maximizing the expected number of LOBs for HFDF receivers. The second is providing a fair share number of HFDF receivers allowed to cover the frequency. The result shown the efficiency of presented model ran by CPLEX toolbox of MATLAB 2020 software.