An (MI)LP-based Primal Heuristic for 3-Architecture Connected Facility Location in Urban Access Network Design

TL;DR

This paper introduces a novel primal heuristic for the complex 3-architecture Connected Facility Location Problem in urban telecommunication networks, effectively reducing optimality gaps compared to existing solvers.

Contribution

It presents an original optimization model incorporating wireless coverage constraints and a hybrid heuristic combining probabilistic fixing and large neighborhood search.

Findings

Heuristic achieves significantly lower optimality gaps.

Model effectively captures wireless coverage in facility location.

Computational results on realistic instances demonstrate superior performance.

Abstract

We investigate the 3-architecture Connected Facility Location Problem arising in the design of urban telecommunication access networks. We propose an original optimization model for the problem that includes additional variables and constraints to take into account wireless signal coverage. Since the problem can prove challenging even for modern state-of-the art optimization solvers, we propose to solve it by an original primal heuristic which combines a probabilistic fixing procedure, guided by peculiar Linear Programming relaxations, with an exact MIP heuristic, based on a very large neighborhood search. Computational experiments on a set of realistic instances show that our heuristic can find solutions associated with much lower optimality gaps than a state-of-the-art solver.