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Andriychuk M. Optimization Algorithms. Classics and Recent Advance 2024
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This volume is devoted to developing algorithm theory and exploring the use of different optimization algorithms for solving various problems in pure science, applied physics, and information technology.
The book consists of two sections. The first focuses on developing abstract algorithms with subsequent applications to real-world optimization problems. It discusses optimization problems based on partial differential equations, canonical polyadic decomposition, variational approach, and ant colony optimization, which are discussed here. The second section presents problems related to optimization in information technologies. Chapters in this section address the utilization of optimization algorithms to solve problems of reducing computation time and computer memory, reducing kernel mechanism processing time in multimedia authoring tools, arranging access optimization for special applications, and minimizing resources for solving vehicle routing problems.
Tensor Products of Ternary Semimodules over Ternary Semifields
On the Classical and Deformed Korteweg-de Vries Equation
Online Canonical Polyadic Decomposition: Application of Fluorescence Tensors with Nonnegative Orthogonality and Sparse Constraint
The Combined Search of the Different Kind of Solutions to the Optimization Problems of Antenna Synthesis Theory
Ant Colony Optimization-Based Models for Agriculture Price Forecasting: Innovations, Case Studies, and Future Prospects
Application of Ant Colony Optimization in Water Resource Management
Fast Particle Search and Positioning Algorithms Using an Efficient Cell Registration Method
Reduction of Kernel Mechanism Processing Time in Multimedia Authoring Tool
Improving the Relevance, Speed, and Computational Efficiency of Semantic Search through Database Indexing: A Review
Paper Recommender System Using Big Data Tools
A Comparative Analysis of Search Algorithms for Solving the Vehicle Routing Problem
An Overview of Ant Colony Optimization Algorithms for Dynamic Optimization Problems