A Global Stochastic Optimization Method for Large Scale
          Problems

W. El Alem; A. El Hami; R. Ellaia

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Displaying similar documents to “A Global Stochastic Optimization Method for Large Scale Problems”

Expériences with Stochastic Algorithms fir a class of Constrained Global Optimisation Problems

Abdellah Salhi, L.G. Proll, D. Rios Insua, J.I. Martin (2010)

RAIRO - Operations Research

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The solution of a variety of classes of global optimisation problems is required in the implementation of a framework for sensitivity analysis in multicriteria decision analysis. These problems have linear constraints, some of which have a particular structure, and a variety of objective functions, which may be smooth or non-smooth. The context in which they arise implies a need for a single, robust solution method. The literature contains few experimental results relevant to such...

Exact and heuristic approaches to solve the Internet shopping optimization problem with delivery costs

Mario C. Lopez-Loces, Jedrzej Musial, Johnatan E. Pecero, Hector J. Fraire-Huacuja, Jacek Blazewicz, Pascal Bouvry (2016)

International Journal of Applied Mathematics and Computer Science

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Internet shopping has been one of the most common online activities, carried out by millions of users every day. As the number of available offers grows, the difficulty in getting the best one among all the shops increases as well. In this paper we propose an integer linear programming (ILP) model and two heuristic solutions, the MinMin algorithm and the cellular processing algorithm, to tackle the Internet shopping optimization problem with delivery costs. The obtained results improve...

High-performance simulation-based algorithms for an alpine ski racer's trajectory optimization in heterogeneous computer systems

Roman Dębski (2014)

International Journal of Applied Mathematics and Computer Science

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Effective, simulation-based trajectory optimization algorithms adapted to heterogeneous computers are studied with reference to the problem taken from alpine ski racing (the presented solution is probably the most general one published so far). The key idea behind these algorithms is to use a grid-based discretization scheme to transform the continuous optimization problem into a search problem over a specially constructed finite graph, and then to apply dynamic programming to find an...

A new nonmonotone adaptive trust region algorithm

Ahmad Kamandi, Keyvan Amini (2022)

Applications of Mathematics

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We propose a new and efficient nonmonotone adaptive trust region algorithm to solve unconstrained optimization problems. This algorithm incorporates two novelties: it benefits from a radius dependent shrinkage parameter for adjusting the trust region radius that avoids undesirable directions and exploits a new strategy to prevent sudden increments of objective function values in nonmonotone trust region techniques. Global convergence of this algorithm is investigated under some mild...

Editorial

Clarisse Dhaenens, Patrick Siarry, El-Ghazali Talbi (2008)

RAIRO - Operations Research

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A novel generalized oppositional biogeography-based optimization algorithm: application to peak to average power ratio reduction in OFDM systems

Sotirios K. Goudos (2016)

Open Mathematics

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A major drawback of orthogonal frequency division multiplexing (OFDM) signals is the high value of peak to average power ratio (PAPR). Partial transmit sequences (PTS) is a popular PAPR reduction method with good PAPR reduction performance, but its search complexity is high. In this paper, in order to reduce PTS search complexity we propose a new technique based on biogeography-based optimization (BBO). More specifically, we present a new Generalized Oppositional Biogeography Based Optimization...

Adaptive thresholding technique for solving optimization problems on attainable sets of (max, min)-linear systems

Mahmoud Gad (2018)

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This article develops a parametric method depend on threshold technique for solving some optimization problems on attainable sets of so called (max, min)-separable linear systems. The concept of attainable set for (max, min)-separable linear equation systems will be introduced. Properties of the attainable sets will be studied in detail. The (max, min) - separable linear equation systems, in which the function of unknown variable occur only on one side, will be consider. The main idea...

Hybrid method for a class of stochastic bi-criteria optimization problems.

Wan, Zhong, Hao, Aiyun, Meng, Fuzheng, Hu, Chaoming (2010)

Journal of Inequalities and Applications [electronic only]

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Meta-optimization of bio-inspired algorithms for antenna array design

Virgilio Zúñiga-Grajeda, Alberto Coronado-Mendoza, Kelly Joel Gurubel-Tun (2018)

Kybernetika

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In this article, a technique called Meta-Optimization is used to enhance the effectiveness of bio-inspired algorithms that solve antenna array synthesis problems. This technique consists on a second optimization layer that finds the best behavioral parameters for a given algorithm, which allows to achieve better results. Bio-inspired computational methods are useful to solve complex multidimensional problems such as the design of antenna arrays. However, their performance depends heavily...

Experiences with stochastic algorithms for a class of constrained global optimisation problems

Abdellah Salhi, L. G. Proll, D. Rios Insua, J. I. Martin (2000)

RAIRO - Operations Research - Recherche Opérationnelle

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On approximating NP-hard optimization problems.

Håstad, Johan (1998)

Documenta Mathematica

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