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Recent Advances in Computational Optimization = Results of the Workshop on Computational Optimization WCO 2020 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Recent Advances in Computational Optimization/ edited by Stefka Fidanova.
其他題名:	Results of the Workshop on Computational Optimization WCO 2020 /
其他作者:	Fidanova, Stefka.
面頁冊數:	XI, 490 p. 95 illus., 51 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-82397-9
ISBN:	9783030823979

Recent Advances in Computational Optimization = Results of the Workshop on Computational Optimization WCO 2020 /
Recent Advances in Computational OptimizationResults of the Workshop on Computational Optimization WCO 2020 /[electronic resource] :edited by Stefka Fidanova. - 1st ed. 2022. - XI, 490 p. 95 illus., 51 illus. in color.online resource. - Studies in Computational Intelligence,9861860-9503 ;. - Studies in Computational Intelligence,564.

Statistical Measurements of Metaheuristics for Solving Engineering Problems -- Heuristic Approaches for the Stochastic Multi-Depot Vehicle Routing Problem with Pickup and Delivery -- Evaluation of MO-ACO Algorithms Using a New Fast Inter-Criteria Analysis Method -- Semantic Graph Queries on Linked Data in Knowledge Graphs -- Online Single-Machine Scheduling via Reinforcement Learning -- Ant Colony Optimization Algorithm for Fuzzy Transport Modelling: InterCriteria Analysis -- Approximation and Exact Algorithms for Multiprocessor Scheduling Problem with Release and Delivery Times -- A Hybrid Method for Scheduling Multiprocessor Tasks on Two Dedicated Processors -- Mathematical Model and its Optimization to Predict the Parameters of Compressive Strength Test -- Optimal Tree of a Complete Weighted Graph -- Simulation of Diffusion Processes in Bimetallic Nanofilms -- On the Problem of Bimetallic Nanostructures Optimization: An Extended Two-Stage Monte Carlo Approach -- An Analysis on the Degrees of Freedom of Binary Representations for Solutions to Discretizable Distance Geometry Problems -- Dynamic Programming for the Synchronization of Energy Production and Consumption Processes -- Reducing the First-type Error Rate of the Log-rank Test: Asymptotic Time Complexity Analysis of an Optimized Test’s Alternative -- Zero Point Approach to Three-Dimensional Intuitionistic Fuzzy Transportation Problem -- On Index-Matrix Interpretation of Interval-Valued Intuitionistic Fuzzy Hamiltonian Cycle -- On the Conceptual Optimization of Generalized Net Models -- Sensitivity Study of a Large-Scale Air Pollution Model by Using Optimized Latin Hyprecube Sampling -- Optimized Quasi-Monte Carlo Methods Based on Van der Corput Sequence for Sensitivity Analysis in Air Pollution Modelling -- Advanced Stochastic Approaches Based on Lattice Rules for Multiple Integrals in Option Pricing -- Advanced Stochastic Approaches for Multidimensional Integrals in Neural Networks -- Improved Stochastic Approaches for Evaluation of the Wigner Kernel -- A Numerical Study on Optimal Monte Carlo Algorithm for Multidimensional Integrals -- Expansions on Quadrature Formulas and Numerical Solutions of Ordinary Differential Equations -- Advanced Stochastic Approaches Based on Lattice Rules for Multiple Integrals in Option Pricing.

This book presents recent advances in computational optimization. Our everyday life is unthinkable without optimization. We try to minimize our effort and to 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 2020. The book includes important real problems like modeling of physical processes, workforce planning, parameter settings for controlling different processes, transportation problems, wireless sensor networks, machine scheduling, air pollution modeling, solving multiple integrals and systems of differential equations which describe real processes, solving engineering problems. It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization problems.

ISBN: 9783030823979

Standard No.: 10.1007/978-3-030-82397-9doiSubjects--Topical Terms:

646849
Artificial Intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Recent Advances in Computational Optimization = Results of the Workshop on Computational Optimization WCO 2020 /
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