Department of Applied Mathematics and Physics Engineering
... In the highly advanced information society today, we encounter various situations that entail modeling, analysis, planning, control and operation of complex and large-scale systems. In these situations, it is extremely important to uncover common mathematical structures shared by those problems whic ...
... In the highly advanced information society today, we encounter various situations that entail modeling, analysis, planning, control and operation of complex and large-scale systems. In these situations, it is extremely important to uncover common mathematical structures shared by those problems whic ...
Multi Objective For Optimal Reactive Power Flow Using Modified
... Optimal reactive power flow (ORPF) plays an important Eberhart 1995[9], this method applied with success to solve role in optimal operation problems of power system[1], the reactive power planning, PSO developed through which referred to assign certain variable such generator simulation of a simplif ...
... Optimal reactive power flow (ORPF) plays an important Eberhart 1995[9], this method applied with success to solve role in optimal operation problems of power system[1], the reactive power planning, PSO developed through which referred to assign certain variable such generator simulation of a simplif ...
H2 Optimal Cooperation of Homogeneous Agents Subject to Delyed
... Recently, we showed that the diagonal-plus-rank-one control structure also appears as the optimal solution to a class of large scale coordination problems, which arise in the control of wind farms (Madjidian and Mirkin, 2014). More specifically, we considered a group of homogeneous agents, where the ...
... Recently, we showed that the diagonal-plus-rank-one control structure also appears as the optimal solution to a class of large scale coordination problems, which arise in the control of wind farms (Madjidian and Mirkin, 2014). More specifically, we considered a group of homogeneous agents, where the ...
Stochastic dominance-constrained Markov decision processes
... constraints, are considered in [36] using convex analytic methods. An inventory system is detailed to motivate the theoretical results. Policies in MDPs induce stochastic processes, and Markov policies induce Markov chains. Typically, policies are evaluated with respect to some measure of expected r ...
... constraints, are considered in [36] using convex analytic methods. An inventory system is detailed to motivate the theoretical results. Policies in MDPs induce stochastic processes, and Markov policies induce Markov chains. Typically, policies are evaluated with respect to some measure of expected r ...
Problem Solving Partnerships using the SARA model
... Newport News, VA in 1984. There, police practitioners, working along with researchers and community members, demonstrated that crime and disorder could be significantly reduced through tailored responses developed as a result of comprehensive analyses of the targeted problems. Police and community m ...
... Newport News, VA in 1984. There, police practitioners, working along with researchers and community members, demonstrated that crime and disorder could be significantly reduced through tailored responses developed as a result of comprehensive analyses of the targeted problems. Police and community m ...
Mathematical optimization
In mathematics, computer science and operations research, mathematical optimization (alternatively, optimization or mathematical programming) is the selection of a best element (with regard to some criteria) from some set of available alternatives.In the simplest case, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and techniques to other formulations comprises a large area of applied mathematics. More generally, optimization includes finding ""best available"" values of some objective function given a defined domain (or a set of constraints), including a variety of different types of objective functions and different types of domains.