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—This paper presents a new approach to economic dispatch (ED) problems with nonsmooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have nonsmooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. In this(More)
—This paper presents an efficient approach for solving economic dispatch (ED) problems with nonconvex cost functions using an improved particle swarm optimization (IPSO). Although the particle swarm optimization (PSO) approaches have several advantages suitable to heavily constrained nonconvex optimization problems, they still can have the drawbacks such as(More)
paper proposes a new binary particle swarm optimization (BPSO) approach inspired from quantum computing, so-called quantum-inspired BPSO (QBPSO), for solving the unit commitment (UC) problems. Although BPSO-based approaches have been successfully applied to the combinatorial optimization problems of power systems, the BPSO algorithm has some drawbacks such(More)
When we were studying phosphorylated proteins in the rat brain after electroconvulsive shock (ECS), we observed the rapid phosphorylation of a 75-kDa protein, which cross-reacted with the anti-phospho-p70 S6 kinase antibody. The phosphorylated protein was purified and identified as moesin, a member of the ezrin/radixin/moesin (ERM) family and a general(More)
Hyaluronic acid (HA) has been implicated in cell adhesion, motility, and tumor progression in gliomas. We previously reported that HA stimulates secretion of matrix metalloproteinase-9 (MMP-9) and induces glioma invasion. However, the molecular mechanism of HA action and therapeutic strategies for blocking HA-induced MMP-9 secretion remain unknown. Here, we(More)
– This paper presents a new approach for thermal unit commitment (UC) using a differential evolution (DE) algorithm. DE is an effective, robust, and simple global optimization algorithm which only has a few control parameters and has been successfully applied to a wide range of optimization problems. However, the standard DE cannot be applied to binary(More)
—This paper presents a development of an improved genetic algorithm (IGA) and its application to a least-cost generation expansion planning (GEP) problem. Least-cost GEP problem is concerned with a highly constrained nonlinear dynamic optimization problem that can only be fully solved by complete enumeration, a process which is computationally impossible in(More)
This paper presents an efficient approach for solving the economic dispatch (ED) problems with valve-point effects using a hybrid particle swarm optimization (PSO) technique. Although PSO-based algorithms are easy to implement and have been empirically shown to perform well on many power system optimization problems, they may get trapped in a local optimum(More)
The demise of the native franchise markets and emergence of competitive markets for electricity generation service is changing the way that electricity is and will be priced and is making increasingly difficult for market participants to appraise the prospects for the future electricity market. As a result, conventional generation expansion planning (GEP)(More)