Advances in Bio-inspired Computing for Combinatorial Optimization Problems:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
2014
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| Schriftenreihe: | Intelligent Systems Reference Library
57 |
| Schlagworte: | |
| Online-Zugang: | BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 UBY01 Volltext Inhaltsverzeichnis Abstract |
| Beschreibung: | "Advances in Bio-inspired Combinatorial Optimization Problems" illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems. Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed. Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive ants; virtual sensitive robots; ant-based techniques for static and dynamic routing problems; stigmergic collaborative agents and learning sensitive agents. This monograph is useful for researchers, students and all people interested in the recent natural computing frameworks. The reader is presumed to have knowledge of combinatorial optimization, graph theory, algorithms and programming. The book should furthermore allow readers to acquire ideas, concepts and models to use and develop new software for solving complex real-life problems |
| Beschreibung: | 1 Online-Ressource (X, 188 p.) 45 illus., 3 illus. in color |
| ISBN: | 9783642401794 |
| DOI: | 10.1007/978-3-642-40179-4 |
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Datensatz im Suchindex
| DE-BY-FWS_katkey | 1015295 |
|---|---|
| _version_ | 1806174812196831232 |
| adam_text | ADVANCES IN BIO-INSPIRED COMPUTING FOR COMBINATORIAL OPTIMIZATION
PROBLEMS
/ PINTEA, CAMELIA-MIHAELA
: 2014
TABLE OF CONTENTS / INHALTSVERZEICHNIS
PART I BIOLOGICAL COMPUTING AND OPTIMIZATION
PART II ANT ALGORITHMS
PART III BIO-INSPIRED MULTI-AGENT SYSTEMS
PART IV APPLICATIONS WITH BIO-INSPIRED ALGORITHMS
PART V CONCLUSIONS AND REMARKS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
ADVANCES IN BIO-INSPIRED COMPUTING FOR COMBINATORIAL OPTIMIZATION
PROBLEMS
/ PINTEA, CAMELIA-MIHAELA
: 2014
ABSTRACT / INHALTSTEXT
ADVANCES IN BIO-INSPIRED COMBINATORIAL OPTIMIZATION PROBLEMS
ILLUSTRATES SEVERAL RECENT BIO-INSPIRED EFFICIENT ALGORITHMS FOR SOLVING
NP-HARD PROBLEMS. THEORETICAL BIO-INSPIRED CONCEPTS AND MODELS, IN
PARTICULAR FOR AGENTS, ANTS AND VIRTUAL ROBOTS ARE DESCRIBED.
LARGE-SCALE OPTIMIZATION PROBLEMS, FOR EXAMPLE: THE GENERALIZED
TRAVELING SALESMAN PROBLEM AND THE RAILWAY TRAVELING SALESMAN PROBLEM,
ARE SOLVED AND THEIR RESULTS ARE DISCUSSED. SOME OF THE MAIN CONCEPTS
AND MODELS DESCRIBED IN THIS BOOK ARE: INNER RULE TO GUIDE ANT SEARCH -
A RECENT MODEL IN ANT OPTIMIZATION, HETEROGENEOUS SENSITIVE ANTS;
VIRTUAL SENSITIVE ROBOTS; ANT-BASED TECHNIQUES FOR STATIC AND DYNAMIC
ROUTING PROBLEMS; STIGMERGIC COLLABORATIVE AGENTS AND LEARNING SENSITIVE
AGENTS. THIS MONOGRAPH IS USEFUL FOR RESEARCHERS, STUDENTS AND ALL
PEOPLE INTERESTED IN THE RECENT NATURAL COMPUTING FRAMEWORKS. THE READER
IS PRESUMED TO HAVE KNOWLEDGE OF COMBINATORIAL OPTIMIZATION, GRAPH
THEORY, ALGORITHMS AND PROGRAMMING. THE BOOK SHOULD FURTHERMORE ALLOW
READERS TO ACQUIRE IDEAS, CONCEPTS AND MODELS TO USE AND DEVELOP NEW
SOFTWARE FOR SOLVING COMPLEX REAL-LIFE PROBLEMS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
| any_adam_object | 1 |
| author | Pintea, Camelia-Mihaela |
| author_facet | Pintea, Camelia-Mihaela |
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| author_variant | c m p cmp |
| building | Verbundindex |
| bvnumber | BV041471061 |
| collection | ZDB-2-ENG |
| contents | Part I Biological Computing and Optimization -- Part II Ant Algorithms -- Part III Bio-inspired Multi-Agent Systems -- Part IV Applications with Bio-inspired Algorithms -- Part V Conclusions and Remarks |
| ctrlnum | (OCoLC)874381862 (DE-599)BVBBV041471061 |
| dewey-full | 006.3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
| dewey-sort | 16.3 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1007/978-3-642-40179-4 |
| format | Electronic eBook |
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| id | DE-604.BV041471061 |
| illustrated | Illustrated |
| indexdate | 2024-08-01T10:55:28Z |
| institution | BVB |
| isbn | 9783642401794 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-026917203 |
| oclc_num | 874381862 |
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| owner | DE-Aug4 DE-92 DE-634 DE-859 DE-898 DE-BY-UBR DE-573 DE-861 DE-706 DE-863 DE-BY-FWS DE-862 DE-BY-FWS |
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| physical | 1 Online-Ressource (X, 188 p.) 45 illus., 3 illus. in color |
| psigel | ZDB-2-ENG |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| record_format | marc |
| series | Intelligent Systems Reference Library |
| series2 | Intelligent Systems Reference Library |
| spellingShingle | Pintea, Camelia-Mihaela Advances in Bio-inspired Computing for Combinatorial Optimization Problems Intelligent Systems Reference Library Part I Biological Computing and Optimization -- Part II Ant Algorithms -- Part III Bio-inspired Multi-Agent Systems -- Part IV Applications with Bio-inspired Algorithms -- Part V Conclusions and Remarks Engineering Artificial intelligence Operations research Computational Intelligence Artificial Intelligence (incl. Robotics) Operation Research/Decision Theory Ingenieurwissenschaften Künstliche Intelligenz Metaheuristik (DE-588)4820176-5 gnd Kombinatorische Optimierung (DE-588)4031826-6 gnd Ameisenalgorithmus (DE-588)4704280-1 gnd |
| subject_GND | (DE-588)4820176-5 (DE-588)4031826-6 (DE-588)4704280-1 |
| title | Advances in Bio-inspired Computing for Combinatorial Optimization Problems |
| title_auth | Advances in Bio-inspired Computing for Combinatorial Optimization Problems |
| title_exact_search | Advances in Bio-inspired Computing for Combinatorial Optimization Problems |
| title_full | Advances in Bio-inspired Computing for Combinatorial Optimization Problems by Camelia-Mihaela Pintea |
| title_fullStr | Advances in Bio-inspired Computing for Combinatorial Optimization Problems by Camelia-Mihaela Pintea |
| title_full_unstemmed | Advances in Bio-inspired Computing for Combinatorial Optimization Problems by Camelia-Mihaela Pintea |
| title_short | Advances in Bio-inspired Computing for Combinatorial Optimization Problems |
| title_sort | advances in bio inspired computing for combinatorial optimization problems |
| topic | Engineering Artificial intelligence Operations research Computational Intelligence Artificial Intelligence (incl. Robotics) Operation Research/Decision Theory Ingenieurwissenschaften Künstliche Intelligenz Metaheuristik (DE-588)4820176-5 gnd Kombinatorische Optimierung (DE-588)4031826-6 gnd Ameisenalgorithmus (DE-588)4704280-1 gnd |
| topic_facet | Engineering Artificial intelligence Operations research Computational Intelligence Artificial Intelligence (incl. Robotics) Operation Research/Decision Theory Ingenieurwissenschaften Künstliche Intelligenz Metaheuristik Kombinatorische Optimierung Ameisenalgorithmus |
| url | https://doi.org/10.1007/978-3-642-40179-4 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026917203&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026917203&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV041145603 |
| work_keys_str_mv | AT pinteacameliamihaela advancesinbioinspiredcomputingforcombinatorialoptimizationproblems |