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They formulated a multi-objective model and solved it using an evolutionary algorithm.
The first part consists in establishing the theoretical model and solved by numerical simulation.
Elegbede and Adjallah (2003) proposed multi-objective availability allocation model and solved through Genetic Algorithm (GA).
The TOM is based on the SIMP material model and solved by sequential linear programming.
The model is developed based on a lumped-parameter model and solved using integral methods.
The problem has been formulated using a linear integer programming model and solved by the CPLEX.
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This paper aims to model and solve two problems at the same time.
We formulate the problem as a set-packing model and solve it using branch-and-price.
Constraint programming is used to model and solve complex combinatorial problems.
Computational fluid dynamics (CFD) have been used to model and solve the ITPTR.
It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.
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