Evolutionary Algorithms for Food Science and Technology（Hardcover）
暫譯: 食品科學與技術的進化演算法（精裝版）

Sparseness and heterogeneity of data are major challenges in the field of food science. Evolutionary algorithms can be effectively used to tackle these issues: in this book, we highlight some promising research directions, based on a collection of case studies from the field.

Researchers and practitioners in food science and technology routinely face several challenges, related to sparseness and heterogeneity of data, as well as to the uncertainty in the measurements and the introduction of expert knowledge in the models. Evolutionary algorithms (EAs), stochastic optimization techniques loosely inspired by natural selection, can be effectively used to tackle these issues. In this book, we present a selection of case studies where EAs are adopted in real-world food applications, ranging from model learning to sensitivity analysis.