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A critical challenge in multi-agent reinforcement learning(MARL) is for multiple agents to efficiently accomplish complex, long-horizon tasks. The agents often have difficulties in cooperating on common goals, dividing complex tasks, and…
This paper proposes a two-phase framework with a B\'{e}zier simplex-based interpolation method (TPB) for computationally expensive multi-objective optimization. The first phase in TPB aims to approximate a few Pareto optimal solutions by…
This paper introduces a novel iterative algorithm for optimizing pilot and data power control (PC) in cell-free massive multiple-input multiple-output (CF-mMIMO) systems, aiming to enhance system performance under real-time channel…
In this paper, we demonstrate a formulation for optimizing coupled submodular maximization problems with provable sub-optimality bounds. In robotics applications, it is quite common that optimization problems are coupled with one another…
Sequences having better autocorrelation properties play a crucial role in enhancing the performance of active sensing systems. Hence, sequences with good autocorrelation properties are very much in demand. In this paper, we addressed the…
Dynamic simulation plays a crucial role in power system transient stability analysis, but traditional numerical integration-based methods are time-consuming due to the small time step sizes. Other semi-analytical solution methods, such as…
This paper studies optimal scheduling and resource allocation under allowable over-scheduling. Formulating an optimisation problem where over-scheduling is embedded, we derive an optimal solution that can be implemented by means of a new…
This paper presents the first parallel implementation of the novel "Interpolated Factored Green Function" (IFGF) method introduced recently for the accelerated evaluation of discrete integral operators arising in wave scattering and other…
In an attempt to improve the utilization efficiency of multi-energy coupling in park-level integrated energy system (PIES), promote wind power consumption and reduce carbon emissions, a low-carbon economic operation optimization model of…
Semiconductor optical amplifiers (SOA) are a fundamental building block for many photonic systems. However, their power inefficiency has been setting back operational cost reduction, and the resulting thermal losses constrain…
In this paper, we consider the (global and sum) energy efficiency optimization problem in downlink multi-input multi-output multi-cell systems, where all users suffer from multi-user interference. This is a challenging problem due to…
An Equivalent Circuit Programming (ECP) approach that expresses the optimality conditions of an optimization problem in terms of an equivalent circuit model and uses circuit simulation techniques to solve for an optimal solution, is applied…
As global attention on renewable and clean energy grows, the research and implementation of microgrids become paramount. This paper delves into the methodology of exploring the relationship between the operational and environmental costs of…
In recent years, various means of efficiently detecting changepoints in the univariate setting have been proposed, with one popular approach involving minimising a penalised cost function using dynamic programming. In some situations, these…
This paper proposes energy-efficient coordinated beamforming strategies for multi-cell multi-user multiple-input single-output system. We consider a practical power consumption model, where part of the consumed power depends on the base…
The transition to the zero-carbon power system is underway accelerating recently. Hydrogen energy and electric vehicles (EVs) are promising solutions on the supply and demand sides. This paper presents a novel architecture that includes…
In this paper, a centralized two-block separable optimization is considered for which a fully parallel primal-dual discrete-time algorithm with fixed step size is derived based on monotone operator splitting method. In this algorithm, the…
The large adoption of EVs brings practical interest to the operation optimization of the charging station. The joint scheduling of pricing and charging control will achieve a win-win situation both for the charging station and EV drivers,…
In recent years, electric vehicle (EV) charging station has experienced an increasing supply-demand mismatch due to its fluctuating renewables and unpredictable charging demand. To reduce its operating cost, this paper proposes a…
This paper presents an algorithm to optimize the parameters of power systems equivalents to enhance the accuracy of the DC power flow approximation in reduced networks. Based on a zonal division of the network, the algorithm produces a…