Recent Advances in Computational Optimization -

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Résumé :
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 volume is a comprehensive collection of extended contributions from the Computational Optimization thematic session, part of the FedCSIS 2024 conference. This book presents recent advances in computational optimization. The volume include important real problems like modelling of physical processes, transportation problems, machine scheduling, air pollution modelling, solving engineering and financial problems, daya optimiation and analysis, modeling and optimization in the field of disaster medicine. 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, application of Generalized nets for modeling and others. This research demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization and decision making problems....

Biographie:

Meteorological and terrain data sources for optimizations of wildfire analyses in Bulgaria.- Customer Segmentation with K-Means Clustering: A Dynamic Approach Using Markov Chains.- Generalized Net for Diabetics Services After Earthquake.- Distribution of Injured People in Hospitals After an Earthquake.- Generalized Net for Disabled Persons Services After Earthquake.- A Software Solution for Package Delivery Optimization in Courier Business Using an Elliptic Intuitionistic Fuzzy Knapsack ProblemImplementation of FIWARE for Development of BigData Elderly Care Platform.- Complete Pareto Front of the Biobjective Minimum Length Minimum Risk Spanning Trees Problem.- Efficient Implementation of Sensitivity Analysis Code of a Large Environmental Model on High Performance Supercomputers.- Leveraging Deep Learning to Forecast Acute Morbidity: Temporal and Spatial Air Pollution Trends.- Electric Vehicle Adoption, Human-Induced Pollution, and Air Quality: Insights from Norway&rsquo...

Sommaire:

Stefka Fidanova is Professor of Computer Science at Institute of Information and Communication Technologies, Bulgarian Academy of Sciences. Her research interests include theory, methods, applications of combinatorial optimization and parallel algorithms. She heads the research group of Parallel Algorithms and Machine Learning. She has authored over 200 refereed journal, proceedings and collection papers, edited 13 proceedings, collections and special issues and written 2 monographs. She belongs to the editorial boards of several international journals. She has received the Career Award 2018 of Marie Curie Alumni Association of EU. She is listed in the World's Top 2% Scientists by Stanford University in 2021.