A Hybrid Exact-ACO Algorithm for the Joint Scheduling, Power and Cluster Assignment in Cooperative Wireless Networks

Abstract

Abstract. Base station cooperation (BSC) has recently arisen as a promising way to increase the capacity of a wireless network. Implementing BSC adds a new design dimension to the classical wireless network design problem: how to define the subset of base stations (clusters) that coordinate to serve a user. Though the problem of forming clusters has been extensively discussed from a technical point of view, there is still a lack of effective optimization models for its representation and algorithms for its solution. In this work, we make a further step towards filling such gap: 1) we generalize the classical network design problem by adding cooperation as an additional decision dimension; 2) we develop a strong formulation for the resulting problem; 3) we define a new hybrid solution algorithm that combines exact large neighborhood search and ant colony optimization. Finally, we assess the performance of our new model and algorithm on a set of realistic instances of a WiMAX network.

A Quantum-Inspired Ant Colony Optimization Algorithm for Parking Lot Rental to Shared E-Scooter Services

“…Here, we presume that the main feature of QACO is to refine the computational behavior of pheromone quantities used by ants for constructing feasible solutions to the problem, both in the initialization and update of pheromone values. The rationale at the basis of using and adapting QACO to our specific problem is that this algorithm provides an effective and efficient way to initialize the pheromone trails, whose setting is known to constitute a tricky task in general ACO (see, e.g., [44][45][46]), by using qubits values that are computed referring to the objective function of the optimization problem. With respect to QACO, we also propose to add an improvement phase at the end of the solution construction phase.…”