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Metaheuristics for multiobjective optimisation. Cooperative approaches, uncertainty handling and application in logistics. (English) Zbl 1217.90160
Summary: This is a summary of the author’s PhD thesis supervised by Laetitia Jourdan and El-Ghazali Talbi (Universit√© Lille, http://sites.google.com/site/arnaudliefooghe/, 2009).
This work deals with the design, implementation and experimental analysis of metaheuristics for solving multiobjective optimisation problems, with a particular interest on hard and large combinatorial problems from the field of logistics. After focusing on a unified view of multiobjective metaheuristics, we propose new cooperative, adaptive and parallel approaches. The performance of these methods are experimented on a scheduling and a routing problem involving two or three objective functions. We finally discuss how to adapt such metaheuristics during the search process in order to handle uncertainty that may occur from many different sources.

90C59 Approximation methods and heuristics in mathematical programming
90C29 Multi-objective and goal programming
90B06 Transportation, logistics and supply chain management
90B50 Management decision making, including multiple objectives
90C27 Combinatorial optimization
Full Text: DOI
[1] Billaut J-C, Moukrim A, Sanlaville E (eds) (2008) Flexibility and robustness in scheduling. Control systems, robotics and manufacturing. Wiley, London
[2] Ehrgott M (2005) Multicriteria optimization, 2nd edn. Springer, New York · Zbl 1132.90001
[3] Figueira JR, Liefooghe A, Talbi E-G, Wierzbicki AP (2010) A parallel multiple reference point approach for multi-objective optimization. Eur J Oper Res (to appear) · Zbl 1188.90237
[4] Jin Y, Branke J (2005) Evolutionary optimization in uncertain environments-a survey. IEEE Trans Evol Comput 9(3): 303–317 · Zbl 05452035 · doi:10.1109/TEVC.2005.846356
[5] Liefooghe A, Basseur M, Jourdan L, Talbi E-G (2007) Combinatorial optimization of stochastic multi-objective problems: an application to the flow-shop scheduling problem. In: Fourth international conference on evolutionary multi-criterion optimization (EMO 2007), vol 4403 of lecture notes in computer science, Springer-Verlag, Matsushima, Japan, pp 457–471
[6] Liefooghe A, Jourdan L, Talbi E-G (2009) A unified model for evolutionary multi-objective optimization and its implementation in a general purpose software framework. In: IEEE symposium on computational intelligence in multicriteria decision-making (IEEE MCDM 2009), Nashville, Tennessee, USA, pp 88–95
[7] Liefooghe A, Jourdan L, Talbi E-G (2010) Metaheuristics and cooperative approaches for the bi-objective ring star problem. Comput Oper Res 37(6): 1033–1044 · Zbl 1178.90266 · doi:10.1016/j.cor.2009.09.004
[8] T’Kindt V, Billaut J-C (2005) Multicriteria scheduling: theory, models and algorithms, 2nd edn. Springer, Berlin
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