Network reconfiguration is an effective approach to reduce the power losses in distribution system. Recent studies have shown that the reconfiguration problem considering load profiles can give a significant improvement on the distribution network performance. This work proposes a novel method to determine the optimal daily configuration based on variable photovoltaic (PV) generation output and the load profile data. A good combination and coordination between these two varying data may give the lowest power loss in the system. Gravitational Search Algorithm (GSA) is applied to determine the optimum tie switches positions for 33-Bus distribution system. GSA based proposed method is also compared with Evolutionary Programming (EP) to examine the effectiveness of GSA algorithm. Obtained results show that the proposed optimal daily configuration method is able to improve the distribution network performance in term of its power loss reduction, number of switching minimization and voltage profile improvement.

Sea freight transportation involves moving huge amounts of freights among maritime locations widely spaced by means of container vessels. The time required to serve container vessels is the most relevant indicator when assessing the competitiveness of a maritime container terminal. In this paper, two main logistic problems stemming from the transshipment of containers in the seaside of a maritime container terminal are addressed, namely, the Berth Allocation Problem aimed at allocating and scheduling incoming vessels into berthing positions along the quay and the Quay Crane Scheduling Problem, whose objective is to schedule the loading and unloading tasks associated with a container vessel. For solving them, two Migrating Birds Optimization (MBO) approaches are proposed. The MBO is a recently proposed nature-inspired algorithm based on the V-formation flight of migrating birds. In this algorithm, a set of solutions of the problem at hand, called birds, cooperate among themselves during the search process by sharing information within a V-line formation. The computational experiments performed over well-known problem instances reported in the literature show that the performance of our proposed MBO approaches is highly competitive and presents a better performance in terms of running time than the best approximate approach proposed in the literature.

A rigorous and novel design procedure is constituted for an ultra-wideband (UWB) low noise amplifier (LNA) by exploiting the 3D electromagnetic simulator based support vector regression machine (SVRM) microstrip line model. First of all, in order to design input and output matching circuits (IMC-OMC), source $Z_S$ and load $Z_L$ termination impedance of matching circuit, which are necessary to obtain required input VSWR ($V_{i\text{req}}$), noise ($F_{\text{req}}$), and gain ($G_{T\text{req}}$), are determined using performance characterisation of employed transistor, NE3512S02, between 3 and 8 GHz frequencies. After the determination of the termination impedance, to provide this impedance with IMC and OMC, dimensions of microstrip lines are obtained with simple, derivative-free, easily implemented algorithm Particle Swarm Optimization (PSO). In the optimization of matching circuits, highly accurate and fast SVRM model of microstrip line is used instead of analytical formulations. ADCH-80a is used to provide ultra-wideband RF choking in DC bias. During the design process, it is aimed that $V_{i\text{req}}$ = 1.85, $F_{\text{req}}$ = $F_{\text{min}}$, and $G_{T\text{req}}$ = $G_{T\text{max}}$ all over operating frequency band. Measurements taken from the realized LNA demonstrate the success of this approximation over the band.