Resource allocation in wireless networks
Journal of High Speed Networks - Special issue: wireless networks
A game theoretic framework for bandwidth allocation and pricing in broadband networks
IEEE/ACM Transactions on Networking (TON)
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Journal of Global Optimization
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Resource Allocation in Wireless Networks: Theory and Algorithms (Lecture Notes in Computer Science)
Resource Allocation in Wireless Networks: Theory and Algorithms (Lecture Notes in Computer Science)
Multiobjective Problem Solving from Nature: From Concepts to Applications (Natural Computing Series)
Multiobjective Problem Solving from Nature: From Concepts to Applications (Natural Computing Series)
Resource allocation in OFDMA wireless communications systems supporting multimedia services
IEEE/ACM Transactions on Networking (TON)
Differential evolution versus genetic algorithms in multiobjective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
An efficient algorithm for computing hypervolume contributions**
Evolutionary Computation
DEMO: differential evolution for multiobjective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Hi-index | 0.00 |
The problem of optimal resource allocation in spatially distributed networks appears, for example, in wireless telecommunications and consists of maximising the network utility, i.e., the fee paid by the users, and minimising the costs of installing the allocated resources. This bi-objective optimisation problem can be approached in several ways, and we investigate the potentials of two fundamentally different ones: a scalar approach that starts with transforming the problem into a single-objective form and then solves it using an appropriate optimisation method, and a vector approach based on evolutionary computation. We provide the problem formulation, present the two approaches and report on numerical experiments and results obtained on test problem instances.