How to Search Optimal Solutions in Big Spaces with Networks of Bio-Inspired Processors

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• 关键词：Natural computing ; Bioinspired computational models ; Networks of bioinspired processors ; Optimization metaheuristics ; Distributed and parallel algorithms
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9094
• 期：1
• 页码：29-39
• 全文大小：203 KB
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• 作者单位：Jos茅 Ram贸n S谩nchez Couso (16)
  Sandra G贸mez Canaval (16)
  David Batard Lorenzo (17)
  
  16. Department of Computer Systems, Universidad Polit茅cnica de Madrid, Crta. de Valencia km. 7, 28031, Madrid, Spain
  17. Department of Research Management, University of Informatics Sciences, Crta. a San Antonio de los Ba帽os, Km. 2.5, La Habana, Cuba
  
• 丛书名：Advances in Computational Intelligence
• ISBN：978-3-319-19258-1
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Searching for new efficient and exact heuristic optimization algorithms in big search spaces currently remains as an open problem. The search space increases exponentially with the problem size, making impossible to find a solution through a mere blind search. Several heuristic approaches inspired by nature have been adopted as suitable algorithms to solve complex optimization problems in many different areas. Networks of Bio-inspired Processors (NBP) is a formal framework formed of highly parallel and distributed computing models inspired and abstracted by biological evolution. From a theoretical point of view, NBP has been proved broadly to be an efficient solving of NP complete problems. The aim of this paper is to explore the expressive power of NBP to solve hard optimization problems with a big search space, using massively parallel architectures. We use the basic concepts and principles of some metaheuristic approaches to propose an extension of the NBP model, which is able to solve actual problems in the optimization field from a practical point of view.