%0 Report %T ParadisEO-MO: From Fitness Landscape Analysis to Efficient Local Search Algorithms %+ Parallel Cooperative Multi-criteria Optimization (DOLPHIN) %+ Centre for Digital Systems (CERI SN - IMT Nord Europe) %+ Laboratoire d'Informatique Fondamentale de Lille (LIFL) %+ Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Groupe SCOBI %A Humeau, Jérémie %A Liefooghe, Arnaud %A Talbi, El-Ghazali %A Verel, Sébastien %N RR-7871 %I INRIA %8 2013 %D 2013 %Z Computer Science [cs]/Operations Research [cs.RO]Reports %X This document presents a general-purpose software framework dedicated to the design, the analysis and the implementation of local search algorithms: ParadisEO-MO. A substantial number of single-solution based local search metaheuristics has been proposed so far, and an attempt of unifying existing approaches is here presented. Based on a fine-grained decomposition, a conceptual model is proposed and is validated by regarding a number of state-of-the-art methodologies as simple variants of the same structure. This model is then incorporated into the ParadisEO-MO software framework. This framework has proven its efficiency and high flexibility by enabling the resolution of many academic and real-world optimization problems from science and industry. %G English %2 https://inria.hal.science/hal-00665421v2/document %2 https://inria.hal.science/hal-00665421v2/file/RR-7871.pdf %L hal-00665421 %U https://inria.hal.science/hal-00665421 %~ UNICE %~ INSTITUT-TELECOM %~ UNIV-LILLE3 %~ CNRS %~ INRIA %~ INRIA-RRRT %~ INRIA-LILLE %~ I3S %~ LIFL %~ INRIA_TEST %~ TESTALAIN1 %~ CRISTAL %~ INRIA2 %~ CRISTAL-DOLPHIN %~ LARA %~ UNIV-COTEDAZUR %~ INSTITUTS-TELECOM %~ IMT-NORD-EUROPE %~ CERI-SN