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The widespread adoption of electric vehicles (EVs) poses challenges associated with charging infrastructures and their impact on the electrical grid. To address these challenges, smart charging approaches have emerged as a key solution that optimizes charging processes and contributes to a smarter and more efficient grid. This paper presents an innovative multi-objective optimization framework for EV smart charging (EVSC) using the Dynamic Hunting Leadership (DHL) method. The framework aims to improve the voltage profile of the system in addition to eliminating voltage violations and energy not supplied (ENS) to EVs within the network. The proposed approach considers both residential EV chargers and parking stations, incorporating realistic EV charger behaviors based on constant current charging and addressing the problem as a mixed integer non-linear programming (MINLP) problem. The performance of the optimization method is evaluated on a distribution network with varying levels of EV penetration connected to the chargers in the grid. The results demonstrate the effectiveness of the DHL algorithm in minimizing conflicting objectives and improving the grid's voltage profile while considering operational constraints. This study provides a road map for EV aggregators and EV owners, guiding them on how to charge EVs based on preferences while minimizing adverse technical impacts on the grid. [ABSTRACT FROM AUTHOR]

A vertex coloring of a graph G $G$ is called distinguishing if no nonidentity automorphisms of G $G$ can preserve it. The distinguishing number of G $G$, denoted by D(G) $D(G)$, is the minimum number of colors required for such a coloring, and the distinguishing threshold of G $G$, denoted by θ(G) $\theta (G)$, is the minimum number k $k$ such that every k $k$‐coloring of G $G$ is distinguishing. As an alternative definition, θ(G) $\theta (G)$ is one more than the maximum number of cycles in the cycle decomposition of automorphisms of G $G$. In this paper, we characterize θ(G) $\theta (G)$ when G $G$ is disconnected. Afterwards, we prove that, although for every positive integer k≠2 $k\ne 2$ there are infinitely many graphs whose distinguishing thresholds are equal to k $k$, we have θ(G)=2 $\theta (G)=2$ if and only if ∣V(G)∣=2 $| V(G)| =2$. Moreover, we show that if θ(G)=3 $\theta (G)=3$, then either G $G$ is isomorphic to one of the four graphs on three vertices or it is of order 2p $2p$, where p≠3,5 $p\ne 3,5$ is a prime number. Furthermore, we prove that θ(G)=D(G) $\theta (G)=D(G)$ if and only if G $G$ is asymmetric, Kn ${K}_{n}$ or Kn¯ $\bar{{K}_{n}}$. Finally, we consider all generalized Johnson graphs, J(n,k,i) $J(n,k,i)$, which are the graphs on all k $k$‐subsets of {1,...,n} $\{1,\ldots ,n\}$ where two vertices A $A$ and B $B$ are adjacent if ∣A∩B∣=k−i $| A\cap B| =k-i$. After studying their automorphism groups and distinguishing numbers, we calculate their distinguishing thresholds as θ(J(n,k,i))=nk−n−2k−1+1 $\theta (J(n,k,i))=\left(\genfrac{}{}{0ex}{}{n}{k}\right)-\left(\genfrac{}{}{0ex}{}{n-2}{k-1}\right)+1$, unless k=n2 $k=\frac{n}{2}$ and i∈{k2,k} $i\in \{\frac{k}{2},k\}$ in which case we have θ(J(n,k,i))=nk $\theta (J(n,k,i))=\left(\genfrac{}{}{0ex}{}{n}{k}\right)$. [ABSTRACT FROM AUTHOR]

In this study, an analytical approach based on bi-level multi-objective game theory is proposed and implemented for dimensional synthesis of the planar crank-rocker four-bar mechanisms. Two players, namely, Stroke (S) and Time Ratio (TR) are considered in the level playing the role of a leader. The third player, Transmission Angle (TA), is placed in a lower level operating with the role of the follower' role. Players' behavior at upper level is also modeled as a cooperative game. In addition to this, the interaction between upper and lower levels is modeled as a Stackelberg game wherein an analytical approach is given to provide an explicit function of the follower's Rational Reaction Set (RRS). Such analytical approach of Stackelberg game theory leads to an interesting relationship of length of the coupler and rocker links. It is, therefore, advised that by adopting equal lengths for coupler link and rocker link, one can guaranty the optimality of the transmission angle deviation, ensuring the Grashof condition. Consequently, the stroke, time ratio, and transmission angle criteria are derived explicitly as mathematical functions explaining the links of mechanism's normalized dimensions. The aforementioned approach coupled with the proposed formulas and charts, greatly simplifies the synthesis of the mechanisms with optimal transmission angle while adopting any desired values of both stroke and time ratio. The theoretical approach proposed are explained with illustrated examples. [ABSTRACT FROM AUTHOR]

The optimum penetration of distributed generations into the distribution grid provides several technical and economic benefits. However, the computational time required to solve the constrained optimization problems increases with the increasing network scale and may be too long for online implementations. This paper presents a parallel solution of a multi-objective distributed generation (DG) allocation and sizing problem to handle a large number of computations. The aim is to find the optimum number of processors in addition to energy loss and DG cost minimization. The proposed formulation is applied to a 33-bus test system, and the results are compared with themselves and with the base case operating conditions using the optimal values and three popular multi-objective optimization metrics. The results show that comparable solutions with high-efficiency values can be obtained up to a certain number of processors. [ABSTRACT FROM AUTHOR]

The integration of distributed generators (DGs), which are based on renewable energy sources, energy storage systems, and static VAR compensators (SVCs), requires considering more challenging operational cases due to the variability of DG production contributed by different characteristics for different time sequences. The size, quantity, technology, and location of DG units have major effects on the system to benefit from the integration. All these aspects create a multi-objective scope; therefore, it is considered a multi-objective mixed-integer optimization problem. This paper presents an improved multi-objective salp swarm optimization algorithm (MOSSA) to obtain multiple Pareto efficient solutions for the optimal number, location, and capacity of DGs and the controlling strategy of SVC a radial distribution system. MOSSA is a bio-inspired optimizer based on swarm intelligence techniques and it is used in finding the optimal solution for a global optimization problem. Two sets of objective functions have been formulated minimizing DGs and SVC cost, voltage violation, energy losses, and system emission cost. The usefulness of the proposed MOSSA has been tested with the 33-bus and 141-bus radial distribution systems and the qualitative comparisons against two well-known algorithms, multiple objective evolutionary algorithms based on decomposition (MOEA/D), and multiple objective particle swarm optimization (MOPSO) algorithm. [ABSTRACT FROM AUTHOR]

In this study, a novel approach based on synergy of cooperative game theory, reliability-based design optimization (RBDO) and Monte Carlo simulation (MCS) is proposed to address the reliability-based multi-objective optimal synthesis of path generating four-bar mechanisms, taking into account the influence of dimensional uncertainty on the reliability of mechanism. Tracking error (T E), deviation of transmission angle from 90° (T A) and probability of failure of Grashof constraint are defined as three performance criteria whose minimization enhance the precision, quality of motion and reliability of mechanism, respectively. To do so, three objective functions are considered, namely, precision ( f T E ), quality of motion ( f T A ) and reliability ( f G ); each objective function is assigned to a player. To conduct the optimization procedure, a game model is proposed, in which the cooperative game scenario is employed by defining a Nash bargaining function to model the interaction between players. In this way, the three-objective optimum design of mechanism is cast into a single-objective optimization problem. The comparisons of the obtained results using the method of this research with those reported in the literature shows a significant improvement in reliability of mechanism, whilst both precision and quality of motion in deterministic design is maintained. Particularly, the tracking error and the deviation of transmission angle from 90° of the synthesized mechanism is 0.0006 and 666.36 respectively, whilst the reliability is guaranteed since no violation of Grashof constraint occurs in the presence of 10% parameter uncertainty. [ABSTRACT FROM AUTHOR]

An effective feature vector generation approach is herein presented based on the cointegration concept and the signal processing methods in order to improve varying speed bearing troubleshooting. Initially, each vibration signal is decomposed into its intrinsic mode functions (IMFs) using ensemble empirical mode decomposition method. Then, the cointegration relations are extracted by applying the Johansen trace test method to the obtained components. In order to form the feature matrix, the cointegration relations are analyzed by wavelet packet transform and the time-domain features are calculated for the wavelet packet coefficients. Consequently, by using a hybrid feature selection approach based on compensation distance evaluation technique, support vector machine, and binary particle swarm optimization algorithm, the optimal hybrid features were identified. The experimental results show that the optimal features are composed of the first cointegration relation, the third level of wavelet packet coefficients, the third IMF, Teager–Kaiser energy, energy, and root mean square. Also, the number of optimal features obtained from the first cointegration relation was less than other relationships. The results reveal that when the optimal feature set is computed for the first cointegration relationship, the identification accuracy of the proposed approach increases considerably. The result analysis also shows the efficiency of the proposed technique in detecting the condition of the bearing in time-varying rotational speed. [ABSTRACT FROM AUTHOR]

In this article, a novel approach based on game theory is presented for multi-objective optimal synthesis of four-bar mechanisms. The multi-objective optimization problem is modelled as a Stackelberg game. The more important objective function, tracking error, is considered as the leader, and the other objective function, deviation of the transmission angle from 90° (TA), is considered as the follower. In a new approach, a group method of data handling (GMDH)-type neural network is also utilized to construct an approximate model for the rational reaction set (RRS) of the follower. Using the proposed game-theoretic approach, the multi-objective optimal synthesis of a four-bar mechanism is then cast into a single-objective optimal synthesis using the leader variables and the obtained RRS of the follower. The superiority of using the synergy game-theoretic method of Stackelberg with a GMDH-type neural network is demonstrated for two case studies on the synthesis of four-bar mechanisms. [ABSTRACT FROM AUTHOR]

In this paper, a fuzzy rule-based system (FRS) has been used for optimal reliability-based robust controller design for a two-mass-spring system with probabilistic uncertainties in its parameters. In this way, a multiobjective uniform-diversity genetic algorithm (MUGA) is first used to find a Pareto front of two-mass-spring system in a deterministic approach. This paper considers a two-mass-spring system under an impulse input. Two conflicting objective functions in this model include settling time of the second mass and control effort exerted on the first mass. Consequently, such Pareto front is then obtained for a two-mass-spring system with probabilistic uncertainties in its parameters using the probabilities of failure of those objective functions through a Monte Carlo simulation approach. It is shown that the FRS system removes the difficulty of selecting suitable crisp values and obligation due to a defining limit state function. Besides, the multiobjective Pareto optimization of such robust controllers using MUGA unveils some very important and informative trade-offs among those objective functions. Consequently, some optimum robust controllers can be compromisingly chosen from the Pareto frontiers. [ABSTRACT FROM PUBLISHER]

Abstract: A subset of the alternating group on points is intersecting if for any pair of permutations in , there is an element such that . We prove if and is intersecting, then . Also, we prove that provided that , then the only sets that meet this bound are the cosets of the stabilizer of a point of . These two results were first proven by Ku and Wong (2007), the proof given in this paper uses an algebraic method that is very different from the original proof. [Copyright &y& Elsevier]

A vertex coloring of a graph G is called distinguishing (or symmetry breaking) if no non-identity automorphism of G preserves it, and the distinguishing number, shown by D (G) , is the smallest number of colors required for such a coloring. This paper is about counting non-equivalent distinguishing colorings of graphs with k colors. A parameter, namely Φ k (G) , which is the number of non-equivalent distinguishing colorings of a graph G with at most k colors, is shown here to have an application in calculating the distinguishing number of the lexicographic product and the X -join of graphs. We study this index (and some other similar indices) which is generally difficult to calculate. Then, we show that if one knows the distinguishing threshold of a graph G , which is the smallest number of colors θ (G) so that, for k ≥ θ (G) , every k -coloring of G is distinguishing, then, in some special cases, counting the number of distinguishing colorings with k colors is very easy. We calculate θ (G) for some classes of graphs including the Kneser graph K (n , 2). We then turn to vertex partitioning by studying the distinguishing coloring partition of a graph G ; a partition of vertices of G which induces a distinguishing coloring for G. There, we introduce Ψ k (G) as the number of non-equivalent distinguishing coloring partitions with at most k cells, which is a generalization to its distinguishing coloring counterpart. [ABSTRACT FROM AUTHOR]