An Estimation of Distribution Algorithm for Flowshop Scheduling with Limited Buffers Mansour Eddaly, Bassem Jarboui, Patrick Siarry, and Abdelwaheb Rebaï Abstract. Most of the works that address the flowshop scheduling problem pre- sume unlimited buffers between successive machines. However, with the advent of new technologies in the manufacturing systems, limited capacity storage between machines has become profitable. Aimed at makespan minimization, the flowshop scheduling problem with buffer constraints is NP-hard in the strong sense. There- fore, several approximate algorithms have been proposed in the literature. In this chapter, we propose an Estimation of Distribution Algorithm for solving a flow- shop scheduling problem with buffer constraints. The main characteristics of the problem, such as the order of jobs and similar blocks of jobs in the sequence, are taken into account while building the probabilistic model. In order to enrich the search procedure of the algorithm, a skewed variable neighbourhood search algo- rithm is embedded into it, restricted by a calculated probability which depends on the quality of the created offspring. The computational results show that our algo- rithm outperforms genetic algorithm and particle swarm algorithm, and can obtain several optimal solutions in a short time. 1 Introduction In a classical flowshop scheduling problem (FSP), each job j ( j = 1, 2, ..., n) must be processed on every machine i (i = 1, 2, ..., m) and all the jobs have to pass through all the machines following the same route. In such problems, an infinite buffer size between every two successive machines is assumed. Due to the modernization of Mansour Eddaly, Bassem Jarboui, and Abdelwaheb Rebaï FSEGS, route de l’aéroport km 4.5, B.P. No. 1088, Sfax 3018, Tunisie e-mail: eddaly.mansour@gmail.com,bassem_jarboui@yahoo.fr, abdelwaheb.rebai@fsegs.rnu.tn Patrick Siarry LiSSi, Université de Paris 12, 61 avenue du Général de Gaulle, 94010 Créteil, France e-mail: siarry@univ-paris12.fr R. Chiong, S. Dhakal (Eds.): Nat. Intel. for Sched., Plan. and Pack. Prob., SCI 250, pp. 89–110. springerlink.com c  Springer-Verlag Berlin Heidelberg 2009