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This paper proposes a Doppler estimation algorithm for underwater acoustic communication by constructing the guide function of the objective function based on linear frequency modulation (LFM) signal. The algorithm employs the least square principle and the particle swarm method, to build the objective function and solves the global optimal solution, respectively. Computer simulations show that the...
The cooperative co-evolution (CC) framework is one of the most efficient methods to solve large scale optimization problems. The traditional CC framework divides decision variables into several mutually-exclusive groups. In this paper, we propose the overlapped cooperative co-evolution (OCC) framework for large scale optimization problems. In OCC framework, the decision variables that have strong...
In this paper, we present a gradient algorithm to identify a damping rate function for a non-Markovian single qubit system. The dynamics of the single qubit system in a non-Markovian environment are assumed to obey a time convolutionless master equation, where all the non-Markovian effects of the environment are combined in the unknown damping rate function. To identify the damping rate function,...
Load balancing is an effective approach to address the spatial-temporal fluctuation of mobile traffic in cellular networks. However, existing schemes that rely on channel borrowing from neighboring cells cannot be directly applied to current LTE-A systems where all cells are deployed with the same spectrum band. In this paper, we consider a multi-cell OFDMA network, where Device-to-Device (D2D) communication...
The massive integration of electric vehicles (EVs) will pose great challenges to the stability and efficiency of both the conventional power networks and transportation systems. The recently emerging smart grid technology, which integrates advanced communication, control, and charging infrastructures, provides promising solutions to tackle these challenges. In this paper, we consider a smart-grid...
Taxi dispatch is a critical issue for taxi company to consider in modern life. This paper formulates the problem into a taxi-passenger matching model and proposes a parallel ant colony optimization algorithm to optimize the model. As the search space is large, we develop a region-dependent decomposition strategy to divide and conquer the problem. To keep the global performance, a critical region is...
The payment scheduling negotiation problem with multi-mode and resource constraints (MRCPSNP) is a practical extension to the resource-constrained project scheduling problem (RCPSP). It considers the interests of both the client and the contractor, who negotiate with each other to maximize their own benefits. Since the interests of the client and contractor are conflicting and the two roles have special...
Human detection plays a crucial role in a number of real world applications. Because of the popularity of smart car, Virtual Reality (VR) and other applications, strong demand of real-time detecting rises. The efficiency of a human detection algorithm becomes more crucial than ever before. In this work, a novel human detection framework combining the Histograms of Oriented Gradients (HOG) feature,...
This paper proposes a novel multi-objective optimization approach for solving multimodal optimization problems (MMOPs). An MMOP at hand is first transformed into a bi-objective optimization problem. The two objectives are constructed totally conflict by using the distance information and the objective function value. In this way, multiple optima of an MMOP are converted into the non-dominated solutions...
Dynamic Traveling salesman problem (DTSP) is a theoretical mathematical model and has been widely applied in dynamic problems in reality. Most of the existing methods used to model DTSP lack a realistic foundation, and cannot provide convenient and polytrophic operations to simulate real-world scenarios. In this paper, a reality-based method is proposed to model DTSP. The model features good controllability...
Timing speculation has recently been proposed as a method for increasing performance beyond that achievable by conventional worst-case design techniques. Starting with the observation of fast temporal variations in timing error probabilities, we propose a run-time technique to dynamically determine the optimal degree of timing speculation (i.e., how aggressively the processor is over-clocked) based...
Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we investigate the tradeoff between two critical but conflicting objectives in multi-user MEC systems, namely, the power consumption of mobile devices and the execution delay...
This paper reviews the recent advances in electromagnetic (EM) modeling and optimization approaches to microwave circuits that exploits parallel computations. The most recent techniques are discussed in this paper including the advanced pole-residue-based neuro-transfer function (neuro-TF) modeling technique and the parallel gradient based EM optimization technique. Using parallel techniques, multiple...
Evolutionary multi-objective optimization (EMO) algorithms have become prevalent and obtained a great success for solving two- or three-objective problems. However, with the number of objectives increases, most of the algorithms cannot perform well due to the expansion of the objective space. Therefore, there is an urgent need for improving EMO algorithms to handle many-objective (four or more objectives)...
Cooperative coevolution framework is an effective strategy to deal with large scale optimization problems. However, most studies on cooperative coevolution framework utilize the same optimizer for all subcomponents, which may not be effective enough. In this paper, we propose a novel multi-optimizer cooperative coevolution method for large scale optimization problems which randomly chooses an optimization...
Microgrids offer a flexible, modular, and scalable solution to facilitate the adoption of renewable energy sources, e.g., solar power, in distribution networks. Noticeably, the cost of daily operation of a microgrid is tightly coupled with its long-term planning decisions, such as the placement of renewable energy sources. This paper studies the optimal placement of solar panels in a grid-connected...
Hybrid precoding is a cost-effective approach to support directional transmissions for millimeter wave (mmWave) communications. While existing works on hybrid precoding mainly focus on single-user single-carrier transmission, in practice multicarrier transmission is needed to combat the much increased bandwidth, and multiuser MIMO can provide additional spatial multiplexing gains. In this paper, we...
This paper presents the design method using topology optimization and the fabricating feasibility using Fused Deposition Modeling (FDM) 3D printing technique for Functionally Graded Material (FGM) insulator. The concepts of FGM and topology optimization are primarily introduced. And a topology optimization approach based on COMSOL Multiphisics is proposed. The optimization objective is to uniform...
Many real-world optimization problems encounter the presence of uncertainties. Dynamic optimization is a class of problems whose fitness functions vary through time. For these problems, evolutionary algorithm is expected to adapt to the changing environments immediately and find the best solution accurately. Besides, most of the environmental changes may not be too drastic in real-world applications,...
Differential evolution (DE) is a simple and efficient evolutionary algorithm for global optimization. In distributed differential evolution (DDE), the population is divided into several sub-populations and each sub-population evolves independently for enhancing population diversity as well as algorithmic performance. Sub-populations in DDE share their elite individuals with neighborhood through a...
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