Results 281 to 290 of about 52,409 (312)

Discrete Methods for Optimal Control Problems

2003
We consider a constrained optimal control problem, which we formulate in classical and in relaxed form. In order to approximate this problem numerically, we apply various discretization schemes on either of these two forms and study the behavior in the limit of discrete optimality and necessary conditions for optimality.
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The Discrete Optimal Assignment Problem

2016
This chapter considers the finite-dimensional case, which is the case when the marginal probability distributions are discrete with finite support. In this case, the Monge–Kantorovich problem becomes a finite-dimensional linear programming problem; the primal and the dual solutions are related by complementary slackness, which is interpreted in terms ...
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Discrete optimization problem

2015
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Discrete Approximations to Continuum Optimal Flow Problems

Studies in Applied Mathematics, 2006
Problems in partial differential equations with inequality constraints can be used to describe a continuum analog to various optimal flow/cut problems. While general concepts from convex optimization (like duality) carry over into continuum problems, the application of ideas and algorithms from linear programming and network flow problems is ...
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Sensitivity analysis for discrete optimal control problems

Mathematical Methods of Operations Research, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Direct Optimization: Problem discretization

2013
The goal of this chapter is to obtain a discretized version of OCP (2.6). We discuss a so-called direct approach and summarize its main advantages and disadvantages in Section 3.1 in comparison with alternative approaches. In Sections 3.2 and 3.3 we discretize OCP (2.6) in two steps. First we discretize in space and obtain a large-scale ODE constrained
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A note on the optimal portfolio problem in discrete processes

Kybernetika, 2009
Summary: We deal with the optimal portfolio problem in discrete-time setting. Employing the discrete Itô formula, which is developed by Fujita, we establish the discrete Hamilton-Jacobi-Bellman (d-HJB) equation for the value function. Simple examples of the d-HJB equation are also discussed.
Naoyuki Ishimura, Yuji Mita
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Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems

Complex & Intelligent Systems, 2021
Qinghua Gu, Naixue Xiong, Song Jiang
exaly  

New binary whale optimization algorithm for discrete optimization problems

Engineering Optimization, 2020
Abdelazim G Hussien, Aboul Ella Hassanien, Essam H Houssein   +2 more
exaly  

Multi-objective metaheuristics for discrete optimization problems: A review of the state-of-the-art

Applied Soft Computing Journal, 2020
Qi Liu, Zhaoxia Guo
exaly