Browsing by Author "Moulai, Mustapha"
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Item Distributed algorithm for finding boundaries of connected components of a Euclidean graph(2017) Bezoui, Madani; Bounceur, Ahcène; Euler, Reinhardt; Moulai, MustaphaItem An empirical study to find the optimal number of security in portfolio selection problem(2016) Bezoui, Madani; Moulai, Mustapha; Bounceur, AhcèneItem Exact method for generating efficient solutions to constrained portfolio assets selection(2014) Bezoui, Madani; Moulai, MustaphaItem An exact method for multiple objective mixed-integer linear programming problem(2011) Amrouche, Salima; Bezoui, Madani; Moulai, MustaphaItem Exact method for solving bi-objective cardinality constrained portfolio selection problem(2016) Bezoui, Madani; Moulai, Mustapha; Bounceur, AhcèneItem A game theory approach to solve linear bi-objective programming problems : application to data collection in WSNs(2017) Bezoui, Madani; Bounceur, Ahcène; Euler, Reinhardt; Moulai, MustaphaItem An iterative method for finding the efficient frontier for a cardinality constrained portfolio assets selection(2015) Bezoui, Madani; Moulai, MustaphaItem A new distributed algorithm for finding dominating sets in IoT networks under multiple criteria(2017) Bezoui, Madani; Bounceur, Ahcène; Euler, Reinhardt; Moulai, MustaphaItem A new hybrid method to maximize the lifetime of coverage in IoT networks(2018) Bezoui, Madani; Bounceur, Ahcène; Euler, Reinhardt; Moulai, MustaphaIn the field of Internet of things and wireless sensor networks, in particular, coverage is a very relevant issue. In this work, we consider the problem of maximizing the lifetime of a wireless sensor network that is required to cover some targets. The idea is to maximize the number of subfamilies that can efficiently cover all the targets. After that, we activate each subfamily alternately to extend the lifetime of the initial network. We then formulate this question as a binary bi-objective programming problem. Finally, we propose a hybrid method using a genetic algorithm and the Monte Carlo procedure based on the work of Bounceur et al. 2012