General

Authors

Search


Committee login



 
 

 


 

 

Forthcoming

Small thumbnail

Baidu SEO

Challenges and Intricacies of Marketing in China

Small thumbnail

Asymmetric Alliances and Information Systems

Issues and Prospects

Small thumbnail

Technicity vs Scientificity

Complementarities and Rivalries

Small thumbnail

Freshwater Fishes

250 Million Years of Evolutionary History

Small thumbnail

Biostatistics and Computer-based Analysis of Health Data using SAS

Biostatistics and Health Science Set

Small thumbnail

Predictive Control

Small thumbnail

Fundamentals of Advanced Mathematics 1

Categories, Algebraic Structures, Linear and Homological Algebra

Small thumbnail

Swelling Concrete in Dams and Hydraulic Structures

DSC 2017

Small thumbnail

The Chemostat

Mathematical Theory of Microorganims Cultures

Small thumbnail

Earthquake Occurrence

Short- and Long-term Models and their Validation

Small thumbnail

Evolutionary Algorithms for Food Science and Technology

Metaheuristics Set – Volume 7

Evelyne Lutton, INRA, France Nathalie Perrot, INRA, France Alberto Tonda, INRA, France

ISBN: 9781848218130

Publication Date: December 2016   Hardback   182 pp.

135 USD


Add to cart

eBooks


Ebook Ebook

Description

Food is an essential component of our lives, health and well-being, not to mention one of the most important sectors of industry, dealing with the chemical, agriculture, animal feed, food processing, trade, retail and consumer sectors. Providing an adequate food supply to a growing world population is one of the grand challenges facing our global society.
In these conditions, robust optimization methods are crucial for reaching breakthrough innovations and sustainable solutions. There is a huge opportunity for evolutionary computation, in particular for developing efficient integrative models and decision support tools, to address the aforementioned challenges.
This book addresses some questions related to optimization in the specific domain of food science, showing how evolutionary computation tools pave the way for new solutions, because of their versatility and robustness, and by offering new ways to better integrate the “human factor”.

Contents

1. Introduction.
2. A Brief Introduction to Evolutionary Algorithms.
3. Model Analysis and Visualization.
4. Interactive Model Learning.
5. Modeling Human Expertise Using Genetic Programming.

About the Authors

Evelyne Lutton received her PhD in 1990 from the Telecom Paris Doctoral School and her habilitation in 1999 from Orsay University. She was a permanent researcher at INRIA (1991-2013) where she headed several research groups, and is now a senior researcher at INRA.
Nathalie Perrot received her PhD in 1997 from the ENSIA (AgroParisTech) Doctoral School, and her habilitation in 2004 from Clermont-Ferrand University. She was a permanent researcher at IRSTEA (1998-2005) and is now a senior researcher at INRA.
Alberto Tonda received his PhD in 2010 from Polytechnic University of Turin, with a thesis on real-world applications of EAs. After post-doctoral work at Institut des Systèmes Complexes Paris and INRIA Saclay, since 2012 he has been a permanent researcher at INRA.

Downloads

DownloadTable of Contents - PDF File - 70 Kb

Related Titles



































0.04177 s.