The transition to clean and low-carbon energy in public buildings is crucial saving green social development. This paper focus on the sustainable development of construction complementary power generation systems existing buildings. In study, it was found that constraints storage system could not be satisfied, which would result failure for purpose peak regulation stable operation microgrid. or...

A multi-objective genetic algorithm is introduced to predict the assignment of protein solid-state NMR (SSNMR) spectra with partial resonance overlap and missing peaks due to broad linewidths, molecular motion, and low sensitivity. This non-dominated sorting genetic algorithm II (NSGA-II) aims to identify all possible assignments that are consistent with the spectra and to compare the relative ...

Constellation design is a typical multiple peaks, multiple valleys and non-linear multi-objective optimization problem. How to design satellite constellation is one of the key sectors of research in the aerospace field. In this paper, in order to improve the global convergence and diversity performance of traditional constellation optimization algorithm, multi-parent arithmetic crossover and SB...

Controllers design problems are multi objective optimization problems as the controller must satisfy several performance measures that are often conflicting and competing with each other. In multi-objective approach a set of solutions can be generated from which the designer can select a final solution according to his requirement and need. This paper presents the design and analysis Proportion...

In the facility location problem usually reducing total transferring cost and time are common objectives. Designing of a network with hub facilities can improve network efficiency. In this study a new model is presented for P-hub covering location problem. In the p-hub covering problem it is attempted to locate hubs and allocate customers to established hubs while allocated nodes to hubs are in...

In Guided Evolutionary Multi-objective Optimization the goal is to find a diverse, but locally focused non-dominated front in a decision maker’s area of interest, as close as possible to the true Paretofront. The optimization can focus its efforts towards the preferred area and achieve a better result [9, 17, 7, 13]. The modeled and simulated systems are often stochastic and a common method to ...

A new multi-objective evolutionary algorithm which can be applied to many nonlinear multi-objective optimization problems is proposed. Its aim is to obtain a discrete fixed size set approximating the complete Pareto-front quickly. It adapts ideas from different multiand single-objective optimization evolutionary algorithms, although it also incorporates new devices, namely, a new method to impr...

Fractional-order proportional-integral-derivative (FOPID) controllers are designed for load-frequency control (LFC) of two interconnected power systems. Conflicting time-domain design objectives are considered in a multi-objective optimization (MOO)-based design framework to design the gains and the fractional differ-integral orders of the FOPID controllers in the two areas. Here, we explore th...

Shape-constrained symbolic regression (SCSR) allows to include prior knowledge into data-based modeling. This inclusion ensure that certain expected behavior is better reflected by the resulting models. The defined via constraints, which refer function form e.g. monotonicity, concavity, convexity or models image boundaries. In addition advantage of obtaining more robust and reliable due definin...

This work presents a method for finding diversity set operating points, which are Pareto optimal and diverse, to digital subscriber lines (DSL). Several works presented in the literature have proposed algorithms for optimizing data transmission in DSL lines, which results in a unique operating point for the modems. These works use spectrum balancing algorithms to solve the power allocation prob...