线性规划
Also known as LP, linear optimization
programming method to achieve the best outcome in a mathematical model
AI overview
Linear programming is a mathematical method for finding the best possible solution to a problem where you need to optimize something (like maximizing profit or minimizing cost) while staying within certain constraints or limits. It matters because it helps businesses and organizations make efficient decisions about how to allocate their resources in real-world situations like production planning, scheduling, and resource management.
AI-generated from the Wikipedia summary — may contain errors.
Research
5,796 papers- Design of complex neuroscience experiments using mixed-integer linear programming.ReviewNeuron · 2021Slivkoff S, Gallant JLDOI: 10.1016/j.neuron.2021.02.019
- Linear Programming from Fibonacci to Farkas.Annals of science · 2021Biggs NDOI: 10.1080/00033790.2020.1811377
- Linear programming: a mathematical tool for analyzing and optimizing children's diets during the complementary feeding period.ReviewJournal of pediatric gastroenterology and nutrition · 2003Briend A, Darmon N, Ferguson E et al.DOI: 10.1097/00005176-200301000-00006
- Linear programming based computational technique for leukemia classification using gene expression profile.PloS one · 2023Ilyas M, Aamir KM, Manzoor S et al.DOI: 10.1371/journal.pone.0292172
Article · 中文
在數學中，線性規劃（Linear Programming，簡稱LP）特指和約束條件皆為線性的最佳化問題。 線性規劃是最優化問題中的一個重要領域。在作業研究中所面臨的許多實際問題都可以用線性規劃來處理，特別是某些特殊情況，例如：網路流、多商品流量等問題，都被認為非常重要。目前已有大量針對線性規劃演算法的研究。很多最佳化問題算法都可以分解為線性規劃子問題，然後逐一求解。在線性規劃的歷史發展過程中所衍伸出的諸多概念，建立了最優化理論的核心思維，例如「對偶」、「分解」、「凸集」的重要性及其一般化等。在微观经济学和商业管理领域中，线性规划亦被大量应用于例如降低生产过程的成本等手段，最終提升產值與營收。對線性規劃有早期貢獻的列昂尼德·维塔利耶维奇·康托罗维奇和特亚林·科普曼斯於1975年共同獲得諾貝爾經濟學獎。
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