This open access book demonstrates all the steps required to design heuristic algorithms for difficult optimization. The classic problem of the travelling salesman is used as a common thread to illustrate all the techniques discussed. This problem is ideal for introducing readers to the subject because it is very intuitive and its solutions can be graphically represented. The book features a we…
This open access book gives a systematic introduction into the spectral theory of differential operators on metric graphs. Main focus is on the fundamental relations between the spectrum and the geometry of the underlying graph. The book has two central themes: the trace formula and inverse problems. The trace formula is relating the spectrum to the set of periodic orbits and is compara…
Many science and engineering applications require the user to find solutions to systems of nonlinear constraints or to optimize a nonlinear function subject to nonlinear constraints. The field of global optimization is the study of methods to find all solutions to systems of nonlinear constraints and all global optima to optimization problems. Numerica is modeling language for global optimizati…
"Online decision making under uncertainty and time constraints represents one of the most challenging problems for robust intelligent agents. In an increasingly dynamic, interconnected, and real-time world, intelligent systems must adapt dynamically to uncertainties, update existing plans to accommodate new requests and events, and produce high-quality decisions under severe time constraints. S…
"A Bradford book."An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications.The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The atte…
A description of perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees.In nearly all machine learning, decisions must be made given current knowledge. Surprisingly, making what is believed to be the best decision is not always the best strategy, even when learning in a supervised learning setting. An emerging body of wo…
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities.The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from hug…
"A thoughtful account of how optimization (also known as theorycrafting or the "moneyballing effect") has changed the way we play games from World of Warcraft to soccer"--OCLC-licensed vendor bibliographic record.
"An accessible and self-contained treatment of the current state of thinking about rationality in economics and other social sciences"--OCLC-licensed vendor bibliographic record.
This book uses resource economics costing approaches incorporating externalities to estimate the returns for the country’s irrigation and demonstrates how underestimating the cost of water leads farmers to overestimate profits. The importance of the subject can be judged in light of the fact that India is the largest user of groundwater both for irrigation and for drinking purposes, pumping t…