The aim of this study is to find the optimal water pressure and percentage of supply vapour in the feed water heaters (fwhs) of steam power plants, such that they maximize the thermal efficiency of the Rankine cycle within pre-specified values of minimum and maximum pressures of the thermodynamic cycle. Thermal efficiency is defined as a function of unknown variables (fluid pressure and vap...

The aim of this study is to find the optimal water pressure and percentage of supply vapour in the feed water heaters (fwhs) of steam power plants, such that they maximize the thermal efficiency of the Rankine cycle within pre-specified values of minimum and maximum pressures of the thermodynamic cycle. Thermal efficiency is defined as a function of unknown variables (fluid pressure and vap...

The problem of short-term scheduling under uncertainty is addressed in this paper through a multiobjective optimization framework that ncorporates economic expectation, robustness, and flexibility in terms of demand satisfaction. In order to be able to identify Pareto optimal olutions, a new approach is applied which is based on normal boundary intersection (NBI) technique. The main advantage o...

It is well known that dynamic OFDMA systems potentially increase the spectral efficiency of wireless systems. They exploit diversity effects in time, space, and frequency by assigning system resources periodically to terminals. Informing the terminals about new assignments creates a signaling overhead. So far, simple signaling schemes have been presented in order to quantify the cost of signali...

We extend some necessary and sufficient conditions for strict local Pareto minima of orderm obtained by Jiménez (2002) to the case of weak ψ-sharp local Pareto minima, i.e., to the case when the local solution is not necessarily unique.

Many optimization problems are naturally delivered in an uncertain framework, and one would like to exercise prudence against the uncertainty elements present in the problem. In previous contributions, it has been shown that solutions to uncertain convex programs that bear a high probability to satisfy uncertain constraints can be obtained at low computational cost through constraints randomiza...

This paper presents a novel decomposition strategy for solving large scale refinery scheduling problems. Instead of formulating one huge and unsolvable MILP or MINLP for centralized problem, we propose a general decomposition scheme that generates smaller sub-systems that canbe solved toglobal optimality. The original problem is decomposed at intermediate storage tanks such that inlet and outle...

Multi-objective optimization yields multiple solutions each of which is no better or worse than the others when the objectives are conflicting. These solutions lie on the Pareto-optimal front which is a lower-dimensional slice of the objective space. Together, the solutions may possess special properties that make them optimal over other feasible solutions. Innovization is the process of extrac...

Lexicase selection is a parent selection method that considers training cases individually, rather than in aggregate, when performing parent selection. Whereas previous work has demonstrated the ability of lexicase selection to solve difficult problems, the central goal of this paper is to develop the theoretical underpinnings that explain its performance. To this end, we derive an analytical f...