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Nanonetworks: The graph theory framework for modeling nanoscale systems

Jelena Živkovic, Bosiljka Tadic (2013)

Nanoscale Systems: Mathematical Modeling, Theory and Applications

Nanonetwork is defined as a mathematical model of nanosize objects with biological, physical and chemical attributes, which are interconnected within certain dynamical process. To demonstrate the potentials of this modeling approach for quantitative study of complexity at nanoscale, in this survey, we consider three kinds of nanonetworks: Genes of a yeast are connected by weighted links corresponding to their coexpression along the cell cycle; Gold nanoparticles, arranged on a substrate, are linked...

Nash equilibrium for a multiobjective control problem related to wastewater management

Néstor García-Chan, Rafael Muñoz-Sola, Miguel Ernesto Vázquez-Méndez (2009)

ESAIM: Control, Optimisation and Calculus of Variations

This paper is concerned with mathematical modelling in the management of a wastewater treatment system. The problem is formulated as looking for a Nash equilibrium of a multiobjective pointwise control problem of a parabolic equation. Existence of solution is proved and a first order optimality system is obtained. Moreover, a numerical method to solve this system is detailed and numerical results are shown in a realistic situation posed in the estuary of Vigo (Spain).


Nash equilibrium payoffs for stochastic differential games with reflection

Qian Lin (2013)

ESAIM: Control, Optimisation and Calculus of Variations

In this paper, we investigate Nash equilibrium payoffs for nonzero-sum stochastic differential games with reflection. We obtain an existence theorem and a characterization theorem of Nash equilibrium payoffs for nonzero-sum stochastic differential games with nonlinear cost functionals defined by doubly controlled reflected backward stochastic differential equations.

Nash ϵ -equilibria for stochastic games with total reward functions: an approach through Markov decision processes

Francisco J. González-Padilla, Raúl Montes-de-Oca (2019)

Kybernetika

The main objective of this paper is to find structural conditions under which a stochastic game between two players with total reward functions has an ϵ -equilibrium. To reach this goal, the results of Markov decision processes are used to find ϵ -optimal strategies for each player and then the correspondence of a better answer as well as a more general version of Kakutani’s Fixed Point Theorem to obtain the ϵ -equilibrium mentioned. Moreover, two examples to illustrate the theory developed are presented....

Nature–inspired metaheuristic algorithms to find near–OGR sequences for WDM channel allocation and their performance comparison

Shonak Bansal, Neena Gupta, Arun Kumar Singh (2017)

Open Mathematics

Nowadays, nature–inspired metaheuristic algorithms are most powerful optimizing algorithms for solving the NP–complete problems. This paper proposes three approaches to find near–optimal Golomb ruler sequences based on nature–inspired algorithms in a reasonable time. The optimal Golomb ruler (OGR) sequences found their application in channel–allocation method that allows suppression of the crosstalk due to four–wave mixing in optical wavelength division multiplexing systems. The simulation results...

Neural networks learning as a multiobjective optimal control problem.

Maciej Krawczak (1997)

Mathware and Soft Computing

The supervised learning process of multilayer feedforward neural networks can be considered as a class of multi-objective, multi-stage optimal control problem. An iterative parametric minimax method is proposed in which the original optimization problem is embedded into a weighted minimax formulation. The resulting auxiliary parametric optimization problems at the lower level have simple structures that are readily tackled by efficient solution methods, such as the dynamic programming or the error...

New algorithms for coupled tasks scheduling – a survey

Jacek Blazewicz, Grzegorz Pawlak, Michal Tanas, Wojciech Wojciechowicz (2012)

RAIRO - Operations Research - Recherche Opérationnelle

The coupled tasks scheduling problem is a class of scheduling problems introduced for beam steering software of sophisticated radar devices, called phased arrays. Due to increasing popularity of such radars, the importance of coupled tasks scheduling is constantly growing. Unfortunately, most of the coupled tasks problems are NP-hard, and only a few practically usable algorithms for such problems were found. This paper provides a survey of already known complexity results of various variants of...

New complexity analysis of a full Nesterov- Todd step infeasible interior-point algorithm for symmetric optimization

Behrouz Kheirfam, Nezam Mahdavi-Amiri (2013)

Kybernetika

A full Nesterov-Todd step infeasible interior-point algorithm is proposed for solving linear programming problems over symmetric cones by using the Euclidean Jordan algebra. Using a new approach, we also provide a search direction and show that the iteration bound coincides with the best known bound for infeasible interior-point methods.

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