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Non-parametric approximation of non-anticipativity constraints in scenario-based multistage stochastic programming

Jean-Sébastien Roy, Arnaud Lenoir (2008)

Kybernetika

We propose two methods to solve multistage stochastic programs when only a (large) finite set of scenarios is available. The usual scenario tree construction to represent non-anticipativity constraints is replaced by alternative discretization schemes coming from non-parametric estimation ideas. In the first method, a penalty term is added to the objective so as to enforce the closeness between decision variables and the Nadaraya–Watson estimation of their conditional expectation. A numerical application...

On approximation in multistage stochastic programs: Markov dependence

Vlasta Kaňková, Martin Šmíd (2004)

Kybernetika

A general multistage stochastic programming problem can be introduced as a finite system of parametric (one-stage) optimization problems with an inner type of dependence. Evidently, this type of the problems is rather complicated and, consequently, it can be mostly solved only approximately. The aim of the paper is to suggest some approximation solution schemes. To this end a restriction to the Markov type of dependence is supposed.

On heuristic optimization.

Ciobanu, Camelia, Marin Gheorghe (2001)

Analele Ştiinţifice ale Universităţii “Ovidius" Constanţa. Seria: Matematică

On the application of insertion techniques for job shop problems with setup times

Yuri N. Sotskov, Thomas Tautenhahn, Frank Werner (2010)

RAIRO - Operations Research

Constructive heuristics for shop scheduling problems are often based on priority (or dispatching) rules. However, recent work has demonstrated that insertion algorithms that step by step insert operations or jobs into partial schedules usually clearly outperform priority rules. In this paper, we consider various job shop scheduling problems with setup times. For each job a specific technological route and a release date are given. Moreover, the jobs are partitioned into groups. A sequence independent...

On the solution of the constrained multiobjective control problem with the receding horizon approach

Daniele De Vito, Riccardo Scattolini (2008)

Kybernetika

This paper deals with a multiobjective control problem for nonlinear discrete time systems. The problem consists of finding a control strategy which minimizes a number of performance indexes subject to state and control constraints. A solution to this problem through the Receding Horizon approach is proposed. Under standard assumptions, it is shown that the resulting control law guarantees closed-loop stability. The proposed method is also used to provide a robustly stabilizing solution to the problem...

Optimization of touristic distribution networks using genetic algorithms.

Josep R. Medina, Víctor Yepes (2003)

SORT

The eight basic elements to design genetic algorithms (GA) are described and applied to solve a low demand distribution problem of passengers for a hub airport in Alicante and 30 touristic destinations in Northern Africa and Western Europe. The flexibility of GA and the possibility of creating mutually beneficial feed-back processes with human intelligence to solve complex problems as well as the difficulties in detecting erroneous codes embedded in the software are described. A new three-parent...

Portfolio optimization for pension plans under hybrid stochastic and local volatility

Sung-Jin Yang, Jeong-Hoon Kim, Min-Ku Lee (2015)

Applications of Mathematics

Based upon an observation that it is too restrictive to assume a definite correlation of the underlying asset price and its volatility, we use a hybrid model of the constant elasticity of variance and stochastic volatility to study a portfolio optimization problem for pension plans. By using asymptotic analysis, we derive a correction to the optimal strategy for the constant elasticity of variance model and subsequently the fine structure of the corrected optimal strategy is revealed. The result...

Primal-dual approximation algorithms for a packing-covering pair of problems

Sofia Kovaleva, Frits C. R. Spieksma (2002)

RAIRO - Operations Research - Recherche Opérationnelle

We consider a special packing-covering pair of problems. The packing problem is a natural generalization of finding a (weighted) maximum independent set in an interval graph, the covering problem generalizes the problem of finding a (weighted) minimum clique cover in an interval graph. The problem pair involves weights and capacities; we consider the case of unit weights and the case of unit capacities. In each case we describe a simple algorithm that outputs a solution to the packing problem and...

Primal-dual approximation algorithms for a packing-covering pair of problems

Sofia Kovaleva, Frits C.R. Spieksma (2010)

RAIRO - Operations Research

We consider a special packing-covering pair of problems. The packing problem is a natural generalization of finding a (weighted) maximum independent set in an interval graph, the covering problem generalizes the problem of finding a (weighted) minimum clique cover in an interval graph. The problem pair involves weights and capacities; we consider the case of unit weights and the case of unit capacities. In each case we describe a simple algorithm that outputs a solution to the packing problem and...

Problèmes fractionnaires : tour d'horizon sur les applications et méthodes de résolution

Anass Nagih, Gérard Plateau (2010)

RAIRO - Operations Research

Fractional programming consists in optimizing a ratio of two functions subject to some constraints. Different versions of this model, linear or nonlinear, have applications in various fields like combinatorial optimization, stochastic programming, data bases, and economy. Three resolution methods are presented: direct solution, parametric approach and solution of an equivalent problem.

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