Population Based Approaches To The Resource Constrained And Discrete Continuous Scheduling
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Population-Based Approaches to the Resource-Constrained and Discrete-Continuous Scheduling
This book addresses two of the most difficult and computationally intractable classes of problems: discrete resource constrained scheduling, and discrete-continuous scheduling. The first part of the book discusses problems belonging to the first class, while the second part deals with problems belonging to the second class. Both parts together offer valuable insights into the possibility of implementing modern techniques and tools with a view to obtaining high-quality solutions to practical and, at the same time, computationally difficult problems. It offers a valuable source of information for practitioners dealing with the real-world scheduling problems in industry, management and administration. The authors have been working on the respective problems for the last decade, gaining scientific recognition through publications and active participation in the international scientific conferences, and their results are obtained using population-based methods. Dr E. Ratajczk-Ropel explores multiple agent and A-Team concepts, while Dr A. Skakovski focuses on evolutionary algorithms with a particular focus on the population learning paradigm.
Knowledge-based Intelligent Information and Engineering Systems
Author: Ignac Lovrek
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-08-18
The three volume set LNAI 5177, LNAI 5178, and LNAI 5179, constitutes the refereed proceedings of the 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008, held in Zagreb, Croatia, in September 2008. The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems; fuzzy and neuro-fuzzy systems; evolutionary computation; machine learning and classical AI; agent systems; knowledge based and expert systems; intelligent vision and image processing; knowledge management, ontologies, and data mining; Web intelligence, text and multimedia mining and retrieval; and intelligent robotics and control.
Agent-Based Optimization
This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.