£107.43

Springer Evolutionary and Memetic Computing for Project Portfolio Selection

Sd-gt31

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Description

Explore advanced computational methods in Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling. Published by Springer as part of the Adaptation, Learning, and Optimization series, this volume provides deep insights into complex optimization problems. This book is designed for researchers and professionals working within the fields of computer science, AI, and machine learning. It covers specific methodologies used to tackle scheduling and selection challenges through evolutionary and memetic computing frameworks. By studying these specialized algorithms, readers gain a better understanding of how adaptation and learning can be applied to real-world project management and technical optimization tasks. This technical resource serves as a valuable addition to academic libraries and professional collections focused on the latest developments in computational intelligence.

Key Features

Focuses on evolutionary and memetic computing techniques for complex project portfolio selection and scheduling tasks.

Part of the specialized Adaptation, Learning, and Optimization series, volume 26, published by Springer.

Provides technical knowledge useful for computer science professionals and researchers in AI and machine learning.

Addresses advanced optimization strategies for managing and scheduling diverse project portfolios effectively.

Product Specifications

Colour
Sd-gt31
Size
2.6' X 5.2'
Format
Paperback
Domain
Amazon UK
Release Date
14 November 2022
Listed Since
24 August 2020

Barcode

No barcode data available

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