相關主題
商品描述
Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners ― including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers ― are interested in solving large-scale MINLP instances.
商品描述(中文翻譯)
許多工程、運營和科學應用包含離散和連續決策變數的混合，以及涉及這些決策變數的非線性關係，這些關係對可行解和最優解的集合有顯著影響。混合整數非線性規劃（Mixed-Integer Nonlinear Programming, MINLP）問題結合了處理非線性函數的數值困難，以及在非凸函數和離散變數的背景下進行優化的挑戰。MINLP 是可用於優化的最靈活建模範式之一；但由於其範圍非常廣泛，在最一般的情況下，它是無法有效解決的。儘管如此，越來越多的研究者和實務工作者 ― 包括化學工程師、運營研究員、工業工程師、機械工程師、經濟學家、統計學家、計算機科學家、運營經理和數學程式設計師 ― 對解決大規模的 MINLP 實例感興趣。
