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Chapitre D'ouvrage Année : 2018

Meeting the Challenges of Optimized Memory Management in Embedded Vision Systems Using Operations Research

Résumé

This book presents new optimization approaches and methods and their application in real-world and industrial problems, and demonstrates how many of the problems arising in engineering, economics and other domains can be formulated as optimization problems. Constituting a comprehensive collection of extended contributions from the 9th International Workshop on Computational Optimization (WCO) held in Gdansk, Poland, September 11–14, 2016, the book discusses important applications such as job scheduling, wildfire modeling, parameter settings for controlling different processes, capital budgeting, data mining, finding the location of sensors in a given network, identifying the conformation of molecules, algorithm correctness, decision support system, and computer memory management. Further, it shows how to develop algorithms for these based on new intelligent methods like evolutionary computations, ant colony optimization and constraint programming. The book is a valuable resource for researchers and practitioners alike.
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Dates et versions

hal-01596331 , version 1 (27-09-2017)

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Paternité - Pas d'utilisation commerciale

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  • HAL Id : hal-01596331 , version 1

Citer

K. Hadj Salem, Y. Kieffer, Stéphane Mancini. Meeting the Challenges of Optimized Memory Management in Embedded Vision Systems Using Operations Research. Recent Advances in Computational Optimization, springer pp.177-205, 2018. ⟨hal-01596331⟩

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