Recent Advances In Computational Optimization
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Recent Advances in Computational Optimization
Our everyday lives are practically unthinkable without optimization. We constantly try to minimize our effort and to maximize the reward or progress achieved. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume presents a comprehensive collection of extended contributions from the 2017 Workshop on Computational Optimization. Presenting recent advances in computational optimization, it addresses important concrete applications, e.g. the modeling of physical processes, wildfire modeling, modeling processes in chemical engineering, workforce planning, wireless access network topology, parameter settings for controlling various processes, berth allocation, identification of homogeneous domains, and quantum computing. The book shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others.
Big Data Optimization: Recent Developments and Challenges
The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.
Recent Advances in Computational Optimization
This book presents recent advances in computational optimization. The book includes important real problems like modelling of physical processes, workforce planning problem, transportation problems, machine scheduling, air pollution modelling, optimization of fast-food restaurant chain, solving engineering, and financial problems. Our everyday life is unthinkable without optimization. We try to minimize our effort and maximize the achieved profit. Many real-world and industrial problems arising in engineering, economics, medicine, and other domains can be formulated as optimization tasks. The book is a comprehensive collection of extended contributions from the Workshops on Computational Optimization 2023. It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming Monte Carlo method, and others. This research demonstrates how some real-world problems arising in engineering, economics, and other domains can be formulated as optimization problems.