Int. J. Metaheuristics, Vol. 3, No. 4, 2014 291 Copyright © 2014 Inderscience Enterprises Ltd. Hybridisation of genetic algorithms and tabu search approach for reconstructing convex binary images from discrete orthogonal projections Mohamed Hadded* TELECOM SudParis, CNRS Samovar UMR 5157, 91011 Evry, France and ENSI, CRISTAL Laboratory, University Campus 2010, Manouba, Tunisia Email: mohamed.hadded@telecom-sudparis.eu *Corresponding author Fethi Jarray and Ghassen Tlig Higher Institute of Computer Science, Gabes University, Madnine, Tunisia and CEDRIC CNAM, 292 Rue Saint-Martin 75003, Paris, France Email: fethi.jarray@cnam.fr Email: ghassen.tlik@gmail.com Hamadi Hasni National School of Computer Science, Manouba University, Tunisia and URAPOP Research Unit, 1060 Unversity Campus, Tunis, Tunisia Email: hamadi.hasni@ensi.rnu.tn Abstract: In this paper, we consider a variant of the NP-complete problem of reconstructing HV-convex binary images from two orthogonal projections, noted by RCBI(H, V). This variant is reformulated as a new integer programming problem. Since this problem is NP-complete, a new hybrid optimisation algorithm combining the techniques of genetic algorithms and tabu search methods, noted by GATS is proposed to find an optimal or an approximate solution for RCBI(H, V) problem. GATS starts from a set of solutions called ‘population’ initialised by using an extension of the network flow model, incorporating a cost function. Two operators, namely crossover and mutation are used to explore the search space, then the quality of each