Algorithms for hard problems: Introduction to combinatorial optimization, randomization, approximation, heuristics: Second Edition. By Juraj Hromkovič. Springer, New York. (2003). 544 pages. $54.95biology and medicinebehaviormiceozoneradiation effects...
组合最优化(Combinatorial Optimization)是应用数学的一个领域,融合了组合数学、线性规划和算法理论中的方法。它一般被应用于解决离散结构(Discrete Structure)中的最优化问题。在组合最优化问题中,我们想要在有限的可行方案中找到最佳的组合方案,这样的最优解可以用图像或者表格的形式,具体地表现出来。但是,组合优化问题的...
Introduction to Linear Optimization 作者:Dimitris Bertsimas/John N. Tsitsiklis 出版社:Athena Scientific 出版年:1997-02-01 页数:608 定价:USD 89.00 装帧:Hardcover ISBN:9781886529199 豆瓣评分 9.1 107人评价 5星 75.7% 4星 17.8% 3星 3.7% 2星
Manifold optimization is ubiquitous in computational and applied mathematics, statistics, engineering, machine learning, physics, chemistry, etc. One of th
Optimization:The exponential amount of information held in a QPU could allow for new methods aimed at finding better solutions to large combinatorial optimization problems, benefitting diverse use cases including route planning, grid optimization, genetics, and portfolio selection. ...
Introduction to Mathematical Optimization (3) : Lagrangian Relaxation and Subgradient Method(Tutorial) Miyamoto Yuichiro 応用数理 23(3), 129-134, 2013-09-25 Y Miyamoto - 《応用数理》 被引量: 0发表: 2013年 Introduction to Mathematical Optimization: From Linear Programming to Metaheuristics This book...
Wiley Series in Discrete Mathematics and Optimization(共29册),这套丛书还有 《Graph Theory》《Combinatorial Optimization》《Maxima and Minima with Applications》《Ramsey Theory, 2nd Edition》《Introduction to Stochastic Search and Optimization》等。 我来说两句 短评 ··· 热门 还没人写过短评呢 我...
The last paper in this set is “Variable Objective Search” by S. Butenko, O. Yezerska, and B. Balasundaram. The authors exploit the notion that many combinatorial optimization problems have alternative objective function formulations while sharing a common feasible region to be searched. While ...
2. Combinatorial problems. The optimization problems expect you to select a feasible solution, so that the value of the required function is minimized or maximized. Combinatorial problems expect you to figure out the number of ways to do something, or the probability of some event happenin...
Memetic algorithms are optimization techniques based on the synergistic combination of ideas taken from different algorithmic solvers, such as population-based search (as in evolutionary techniques) and local search (as in gradient-ascent techniques). Af