Estimation of distribution algorithms in logistics : Analysis, design, and application

This thesis considers the analysis, design and application of Estimation of Distribution Algorithms (EDA) in Logistics. It approaches continouos nonlinear optimization problems (standard test problems and stochastic transportation problems) as well as location problems, strategic safety stock placement problems and lotsizing problems. The thesis adds to the existing literature by proposing theoretical advances for continuous EDAs and practical applications of discrete EDAs. Thus, it should be of interest for researchers from evolutionary computation, as well as practitioners that are in need of efficient algorithms for the above mentioned problems.

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