Multiobjective variational programming under generalized (V,ρ)-B-type I functions
Multiparametric linear fractional functionals programming.
In this paper a multiparametric linear fractional functionals program, with parameters appearing only in the objective function, is generated. The optimum solution of this parametric program is supposed to satisfy the constraints as equations only. It is also shown that the set of parameters forms a convex polyhedron.
Multiperiod medians on networks
Multiple criteria assignment problem : combining the collective criterion with individual preferences
Multiple Criteria Decision Making for Power Generation Investment Planning Under Restrictions of Aggregate Emission Control
Multiple objective optimization of hydro-thermal systems using Ritz's method.
Multiple routing strategies in a labelled network
We present here models and algorithms for the construction of efficient path systems, robust to possible variations of the characteristics of the network. We propose some interpretations of these models and proceed to numerical experimentations of the related algorithms. We conclude with a discussion of the way those concepts may be applied to the design of a Public Transportation System.
Multiple Routing Strategies in a Labelled Network
We present here models and algorithms for the construction of efficient path systems, robust to possible variations of the characteristics of the network. We propose some interpretations of these models and proceed to numerical experimentations of the related algorithms. We conclude with a discussion of the way those concepts may be applied to the design of a Public Transportation System.
Multiplicateurs de Kuhn-Tucker pour des jeux non coopératifs contraints
Multistage multivariate nested distance: An empirical analysis
Multistage stochastic optimization requires the definition and the generation of a discrete stochastic tree that represents the evolution of the uncertain parameters in time and space. The dimension of the tree is the result of a trade-off between the adaptability to the original probability distribution and the computational tractability. Moreover, the discrete approximation of a continuous random variable is not unique. The concept of the best discrete approximation has been widely explored and...
Multistage stochastic programs: The state-of-the-art and selected bibliography
Multistage stochastic programs via autoregressive sequences and individual probability constraints
The paper deals with a special case of multistage stochastic programming problems. In particular, the paper deals with multistage stochastic programs in which a random element follows an autoregressive sequence and constraint sets correspond to the individual probability constraints. The aim is to investigate a stability (considered with respect to a probability measures space) and empirical estimates. To achieve new results the Wasserstein metric determined by norm and results of multiobjective...
Multi-swarm that learns
Multi-working modes product-color planning based on evolutionary algorithms and swarm intelligence.
Nanonetworks: The graph theory framework for modeling nanoscale systems
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
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
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 -equilibria for stochastic games with total reward functions: an approach through Markov decision processes
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 -equilibrium. To reach this goal, the results of Markov decision processes are used to find -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 -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
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...
Necessary and sufficient optimality conditions for average reward of controlled Markov chains