The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

The search session has expired. Please query the service again.

Displaying similar documents to “The nonlinear complementarity model of industrial symbiosis network equilibrium problem”

Modeling acquaintance networks based on balance theory

Vida Vukašinović, Jurij Šilc, Riste Škrekovski (2014)

International Journal of Applied Mathematics and Computer Science

Similarity:

An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB) model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors...

A comparative and experimental study on gradient and genetic optimization algorithms for parameter identification of linear MIMO models of a drilling vessel

Stanisław Bańka, Michał Brasel, Paweł Dworak, Krzysztof Jaroszewski (2015)

International Journal of Applied Mathematics and Computer Science

Similarity:

The paper presents algorithms for parameter identification of linear vessel models being in force for the current operating point of a ship. Advantages and disadvantages of gradient and genetic algorithms in identifying the model parameters are discussed. The study is supported by presentation of identification results for a nonlinear model of a drilling vessel.

A globally convergent neurodynamics optimization model for mathematical programming with equilibrium constraints

Soraya Ezazipour, Ahmad Golbabai (2020)

Kybernetika

Similarity:

This paper introduces a neurodynamics optimization model to compute the solution of mathematical programming with equilibrium constraints (MPEC). A smoothing method based on NPC-function is used to obtain a relaxed optimization problem. The optimal solution of the global optimization problem is estimated using a new neurodynamic system, which, in finite time, is convergent with its equilibrium point. Compared to existing models, the proposed model has a simple structure, with low complexity....

A variational model for equilibrium problems in a traffic network

Giandomenico Mastroeni, Massimo Pappalardo (2010)

RAIRO - Operations Research

Similarity:

We propose a variational model for one of the most important problems in traffic networks, namely, the network equilibrium flow that is, traditionally in the context of operations research, characterized by minimum cost flow. This model has the peculiarity of being formulated by means of a suitable variational inequality (VI) and its solution is called “equilibrium”. This model becomes a minimum cost model when the cost function is separable or, more general, when the Jacobian of the...

Modelling Evolution of Regulatory Networks in Artificial Bacteria

Y. Sanchez-Dehesa, D. Parsons, J. M. Peña, G. Beslon (2008)

Mathematical Modelling of Natural Phenomena

Similarity:

Studying the evolutive and adaptative machanisms of prokayotes is a complicated task. As these machanisms cannot be easily studied "in vivo", it is necessary to consider other methods. We have therefore developed the RAevol model, a model designed to study the evolution of bacteria and their adaptationto the environment. Our model simulates the evolution of a population of artificial bacteria in a changing environment, providing us with an insight into the strategies that digital organisms...

Multiperiod supply chain network equilibrium model with electronic commerce and multicriteria decision-making

Guoshan Liu, Shiqin Xu (2012)

RAIRO - Operations Research - Recherche Opérationnelle

Similarity:

In this paper, we develop a supply chain network equilibrium model in which electronic commerce in the presence of both B2B (business-to-business) and B2C (business-to-consumer) transactions, multiperiod decision-making and multicriteria decision-making are integrated. The model consists of three tiers of decision-makers (manufacturers, retailers and consumers at demand markets) who compete within a tier but may cooperate between tiers. Both manufacturers and retailers are concerned...

Nonlinear predictive control based on neural multi-models

Maciej Ławryńczuk, Piotr Tatjewski (2010)

International Journal of Applied Mathematics and Computer Science

Similarity:

This paper discusses neural multi-models based on Multi Layer Perceptron (MLP) networks and a computationally efficient nonlinear Model Predictive Control (MPC) algorithm which uses such models. Thanks to the nature of the model it calculates future predictions without using previous predictions. This means that, unlike the classical Nonlinear Auto Regressive with eXternal input (NARX) model, the multi-model is not used recurrently in MPC, and the prediction error is not propagated....

Using normal mode analysis in teaching mathematical modeling to biology students

D. A. Kondrashov (2011)

Mathematical Modelling of Natural Phenomena

Similarity:

Linear oscillators are used for modeling a diverse array of natural systems, for instance acoustics, materials science, and chemical spectroscopy. In this paper I describe simple models of structural interactions in biological molecules, known as elastic network models, as a useful topic for undergraduate biology instruction in mathematical modeling. These models use coupled linear oscillators to model the fluctuations of molecular structures around the equilibrium state. I present many...

Efficient nonlinear predictive control based on structured neural models

Maciej Ławryńczuk (2009)

International Journal of Applied Mathematics and Computer Science

Similarity:

This paper describes structured neural models and a computationally efficient (suboptimal) nonlinear Model Predictive Control (MPC) algorithm based on such models. The structured neural model has the ability to make future predictions of the process without being used recursively. Thanks to the nature of the model, the prediction error is not propagated. This is particularly important in the case of noise and underparameterisation. Structured models have much better long-range prediction...

Systemic risk through contagion in a core-periphery structured banking network

Oliver Kley, Claudia Klüppelberg, Lukas Reichel (2015)

Banach Center Publications

Similarity:

We contribute to the understanding of how systemic risk arises in a network of credit-interlinked agents. Motivated by empirical studies we formulate a network model which, despite its simplicity, depicts the nature of interbank markets better than a symmetric model. The components of a vector Ornstein-Uhlenbeck process living on the nodes of the network describe the financial robustnesses of the agents. For this system, we prove a LLN for growing network size leading to a propagation...