论文信息 - Supply Chain Planning under Uncertainty using Genetic Algorithms

Supply Chain Planning under Uncertainty using Genetic Algorithms

Abstract The solution of a mixed integer linear programming (MILP) model describing the main characteristics of the basic Supply Chain Management (SCM) problem is attained using different procedures. The use of genetic algorithms is proposed as a computing efficient alternative to deal with the combinatorial explosion of alternatives associated to the consideration of different production scenarios, which is a requirement if, as usual, the basic planning information is just estimated with a significant degree of uncertainty.

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