Abstract
In general, many of the problems that we must resolve in real life must be addressed in a multiobjective way because we often have conflicting objectives (particular objective functions) where it is possible to compute more than one optimal solution. Such solutions are called nondominated or Pareto-optimal solutions. Each Pareto-optimal solution can be considered as a final “compromise” solution of a multiobjective optimization (MOO) problem because it has no a priori advantage over other Pareto-optimal solutions. Therefore, the ability to compute the maximum possible Pareto-optimal solutions is very important. The purpose of multiobjective optimization is ideally to generate the set of solutions involving optimal trade-offs among the different objectives.
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Holdsworth, S.D., Simpson, R. (2016). Multiobjective Optimization in Thermal Food Processing. In: Thermal Processing of Packaged Foods. Food Engineering Series. Springer, Cham. https://doi.org/10.1007/978-3-319-24904-9_20
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DOI: https://doi.org/10.1007/978-3-319-24904-9_20
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