This paper concentrates on characterizing energy, latency and capacity trade-offs in multi-hop wireless ad-hoc networks. Therefore, a multiobjective framework is proposed to derive...
Jean-Marie Gorce, Ruifeng Zhang, Katia Jaffr&egrav...
The resolution of a Multi-Objective Optimization Problem (MOOP) does not end when the Pareto-optimal set is found. In real problems, a single solution must be selected. Ideally, t...
The Data Driven Design Optimization Methodology (DDDOM) is a Dynamic Data Driven Application System (DDDAS) developed for engineering design optimization. The DDDOM synergizes expe...
Negotiation techniques have been demonstrated to be effective in solving complex multi-objective problems. When the optimization process operates on continuous variables, it can b...
We develop a novel coevolutionary algorithm based upon the concept of Pareto optimality. The Pareto criterion is core to conventional multi-objective optimization (MOO) algorithms....