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Mohamed-Mahmoud Ould-Sidi Memmah

Mohamed-Mahmoud Ould-Sidi Memmah


Agreenskills
session, year:
2013 1st

Status:
Former fellow

Receiving laboratory:
University of Birmingham

Country of origin:

France

Country of destination:

United Kingdom

Last available contact

Email(s):
mmouldsidi@avignon.inra.fr

CV:
Download Curriculum Vitae

Mobility project

Meta-heuristics for the model-based design of integrated cropping systems

The model-based design of Integrated Cropping Systems (ICS) is an objective of my home research unit PSH. It aims to identify all combinations of a number of technical actions to be implemented to satisfy a set of nonlinear and conflicting objectives (environmental protection, economic viability, organoleptic quality, ecological restoration) subject to strong constraints. Therefore, the model-based design of ICS is studied as a multi-objective constrained optimization problem. This is a difficult optimization problem where there are no explicit analytical mathematical formulas of the objectives’ functions in terms of the decision variables. This class of optimization problems is thus intractable using classical optimization methods. Many bio-inspired meta-heuristics, e.g. Evolutionary Algorithms (EAs), ant colonies, the particle swarm optimization and artificial immune systems, have been proposed to tackle very hard optimization problems. These algorithms have been deeply used in experimental studies and have often produced efficiently good quality solutions. Unfortunately, the rare theoretical studies of these algorithms are mainly restricted to very simple forms of evolutionary algorithms. Theory is important because it gives us accurate and deeper understanding of why, how and when meta-heuristics work effectively. This information could lead to the design of new algorithms and their successful applications to new optimisation problems.

This is the focus of an ongoing project at CERIA studying theoretically what types of problems can be solved using what kind of EAs, and why. The relationship between problem characteristics and algorithmic parameters is particularly investigated. Five population-based meta-heuristics are studied and many optimization problems are considered as case studies. Three case studies that would be investigated during the stay relate the model-based design of ICS and deal with pesticide use reduction, landscape ecosystem services and sustainability, and fruit breeding.

Biography & research interests

My research focuses on the development of multi-objective optimization algorithms and their applications to many realworld problems. During my PhD at Centrale Lille supervised by Professor P. Borne, I was interested in the real-time regulation of urban collective transportation networks. As a postdoctoral researcher at Université du Littoral Côte d’Opale and GDF, I had worked on the optimal design and dimensioning of hydrogen distribution pipeline networks. As an INRA permanent researcher in the PSH unit, I am studying the model-based design of Integrated Cropping production Systems (ICS) as difficult multi-objective optimization problems. This approach interfaces models describing the cropping systems with meta-heuristics algorithms. The used models describe either the interactions between plants, pests, and natural enemies under the effect of cultural and land use practices, or the interactions between genotypes, environments and cultural practices. Our short-term objective is to propose efficient algorithms able to solve these kinds of optimization problems. Afterwards, we will propose effective cultural procedures and land use scenarios satisfying many antagonist criteria (economic, environmental, ecological, and agronomic) and fulfilling some biotic and abiotic constraints.

Selected publications

Dario Constantinescu, Mohamed-Mahmoud Memmah, Gilles Vercambre, Michel Génard, Valentina Baldazzi, Mathilde Causse, Elise Albert, Béatrice Brunel, Pierre Valsesia, Nadia Bertin, 2016. Model-Assisted Estimation of the Genetic Variability in Physiological Parameters Related to Tomato Fruit Growth under Contrasted Water Conditions. Frontiers in Plant Science 12/2016; 1(7). Doi: 10.3389/ fpls.2016.01841.

Bénédicte Quilot-Turion, Michel Génard, Pierre Valsesia, Mohamed-Mahmoud Memmah, 2016. Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model. Frontiers in Plant Science 12/2016; 7(1603.03238v1). Doi: 10.3389/fpls.2016.01873.

Mohamed-Mahmoud Memmah, Francoise Lescourret, Xin Yao, Claire Lavigne, 2015. Metaheuristics for agricultural land use optimization. A review. Agronomy for Sustainable Development 05/2015; 35(3):975-998. Doi: 10.1007/ s13593-015-0303-4.

M. Génard, B. Quilot-Turion, M.M. Ould Sidi, A. Kadrani, N. Hilgert, F. Lescourret, 2015.Heuristic value of a "Virtual Fruit" model of peach fruit quality and sensitivity to brown rot: Impact of a single mutation and design of ideotypes. Acta horticulturae 02/2015; 1068(1068):253-260. Doi: 10.17660/ActaHortic.2015.1068.31.

I. Grechi, N. Hilgert, M.M. Ould Sidi, F. Lescourret, 2015. An agro-ecological model of the peach tree-Myzus persicae aphid system and its use to evaluate and design integrated management scenarios. Acta horticulturae, 1068(1068):4350. Doi:10.17660/ActaHortic.2015.1068.4.

Talks in annual meetings

Keywords

Model-based design, integrated production systems, optimisation, evolutionary algorithms, multiobjective optimisation, algorithm design, complexity analysis