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Parallel Problem Solving from Nature, PPSN XI: 11th International Conference, Krakov, Poland, September 11-15, 2010, Proceedings, Part II de Robert Schaefer

Parallel Problem Solving from Nature, PPSN XI: 11th International Conference, Krakov, Poland, September 11-15, 2010, Proceedings, Part II: Lecture Notes in Computer Science, cartea 6239

Editat de Robert Schaefer, Carlos Cotta, Joanna Kolodziej, Günter Rudolph
en Limba Engleză Paperback – 3 sep 2010

Relevanța acestui volum pentru cercetătorii care urmăresc acreditări academice în informatică și inteligență artificială este dată de rigoarea științifică a seriei Lecture Notes in Computer Science. Volumul de față, Parallel Problem Solving from Nature, PPSN XI, reprezintă a doua parte a lucrărilor celei de-a 11-a conferințe internaționale PPSN, un eveniment de referință pentru comunitatea calculului natural. Suntem de părere că selecția strictă a celor 128 de lucrări dintr-un total de 232 de propuneri garantează un nivel calitativ înalt, esențial pentru literatura de specialitate.

Această ediție extinde cadrul propus de Artificial Evolution de Jin-Kao Hao cu date noi din perioada 2010, axându-se pe o diversitate mai mare de metaheuristici și sisteme bio-inspirate. În timp ce alte lucrări similare se concentrează pe algoritmi genetici clasici, Parallel Problem Solving from Nature, PPSN XI explorează frontierele interdependenței dintre modelarea dependențelor și structura problemelor, folosind generatoare de peisaje randomizate pentru a compara performanța algoritmilor.

Structura volumului este una tematică, debutând cu o secțiune densă dedicată teoriei calculului evolutiv. Primele capitole analizează riguros aspecte precum convergența log-liniară și ratele de mutație adaptive pentru probleme specifice (LeadingOnes), progresând apoi către analiza peisajelor de fitness și benchmarking. Această organizare permite cititorului o tranziție logică de la fundamentele matematice la aplicații complexe, precum optimizarea funcțiilor monotone și utilizarea matricelor de covarianță în mutațiile diferențiale. Editura Springer Berlin, Heidelberg menține standardul tehnic ridicat prin includerea de grafice și demonstrații matematice esențiale pentru înțelegerea limitelor inferioare ale timpului de execuție pentru algoritmii evolutivi.

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Specificații

ISBN-13: 9783642158704
ISBN-10: 3642158706
Pagini: 578
Ilustrații: XXII, 556 p. 182 illus.
Dimensiuni: 12 x 91 x 30 mm
Greutate: 0.86 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Professional/practitioner

De ce să citești această carte

Această resursă este indispensabilă profesioniștilor și cercetătorilor din domeniul calculului bio-inspirat. Cititorul câștigă acces la metodologii de peer-review riguroase și la soluții de ultimă oră pentru probleme de optimizare complexă. Este un instrument valoros pentru cei care doresc să înțeleagă fundamentele teoretice ale inteligenței colective și să aplice algoritmi memetici în scenarii reale, oferind un avantaj competitiv în cercetarea academică și dezvoltarea de software avansat.

Cuprins

Multiobjective Optimization, Models and Applications.- A Novel Smart Multi-Objective Particle Swarm Optimisation Using Decomposition.- A Hybrid Scalarization and Adaptive ?-Ranking Strategy for Many-Objective Optimization.- pMODE-LD+SS: An Effective and Efficient Parallel Differential Evolution Algorithm for Multi-Objective Optimization.- Improved Dynamic Lexicographic Ordering for Multi-Objective Optimisation.- Privacy-Preserving Multi-Objective Evolutionary Algorithms.- Optimizing Delivery Time in Multi-Objective Vehicle Routing Problems with Time Windows.- Speculative Evaluation in Particle Swarm Optimization.- Towards Directed Open-Ended Search by a Novelty Guided Evolution Strategy.- Consultant-Guided Search Algorithms with Local Search for the Traveling Salesman Problem.- Many-Objective Test Problems to Visually Examine the Behavior of Multiobjective Evolution in a Decision Space.- Preference-Based Multi-Objective Particle Swarm Optimization Using Desirabilities.- GPGPU-Compatible Archive Based Stochastic Ranking Evolutionary Algorithm (G-ASREA) for Multi-Objective Optimization.- Hybrid Directional-Biased Evolutionary Algorithm for Multi-Objective Optimization.- A Framework for Incorporating Trade-Off Information Using Multi-Objective Evolutionary Algorithms.- Applications, Engineering and Economical Models.- Topography-Aware Sensor Deployment Optimization with CMA-ES.- Evolutionary Optimization on Problems Subject to Changes of Variables.- On-Line Purchasing Strategies for an Evolutionary Algorithm Performing Resource-Constrained Optimization.- Parallel Artificial Immune System in Optimization and Identification of Composite Structures.- Bioreactor Control by Genetic Programming.- Solving the One-Commodity Pickup and Delivery Problem Using an Adaptive HybridVNS/SA Approach.- Testing the Dinosaur Hypothesis under Empirical Datasets.- Fractal Gene Regulatory Networks for Control of Nonlinear Systems.- An Effective Hybrid Evolutionary Local Search for Orienteering and Team Orienteering Problems with Time Windows.- Discrete Differential Evolution Algorithm for Solving the Terminal Assignment Problem.- Decentralized Evolutionary Agents Streamlining Logistic Network Design.- Testing the Permutation Space Based Geometric Differential Evolution on the Job-Shop Scheduling Problem.- New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization.- Evolving a Single Scalable Controller for an Octopus Arm with a Variable Number of Segments.- Multi-agent Systems and Parallel Approaches.- An Island Model for the No-Wait Flow Shop Scheduling Problem.- Environment-Driven Embodied Evolution in a Population of Autonomous Agents.- Large-Scale Global Optimization Using Cooperative Coevolution with Variable Interaction Learning.- EvoShelf: A System for Managing and Exploring Evolutionary Data.- Differential Evolution Algorithms with Cellular Populations.- Flocking in Stationary and Non-stationary Environments: A Novel Communication Strategy for Heading Alignment.- Evolution of XPath Lists for Document Data Selection.- PMF: A Multicore-Enabled Framework for the Construction of Metaheuristics for Single and Multiobjective Optimization.- Parallel Evolutionary Approach of Compaction Problem Using MapReduce.- Ant Colony Optimization with Immigrants Schemes in Dynamic Environments.- Secret Key Specification for a Variable-Length Cryptographic Cellular Automata Model.- Variable Neighborhood Search and Ant Colony Optimization for the Rooted Delay-Constrained Minimum Spanning Tree Problem.- Adaptive Modularization of the MAPK Signaling Pathway Using the Multiagent Paradigm.- Genetic Computing and Games.- Experimental Comparison of Methods to Handle Boundary Constraints in Differential Evolution.- Entropy-Driven Evolutionary Approaches to the Mastermind Problem.- Evolutionary Detection of New Classes of Equilibria: Application in Behavioral Games.- Design and Comparison of two Evolutionary Approaches for Solving the Rubik’s Cube.- Statistical Analysis of Parameter Setting in Real-Coded Evolutionary Algorithms.- Performance of Network Crossover on NK Landscapes and Spin Glasses.- Promoting Phenotypic Diversity in Genetic Programming.- A Genetic Programming Approach to the Matrix Bandwidth-Minimization Problem.- Using Co-solvability to Model and Exploit Synergetic Effects in Evolution.- Fast Grammar-Based Evolution Using Memoization.- Evolution of Conventions and Social Polarization in Dynamical Complex Networks.- Evolving Strategies for Updating Pheromone Trails: A Case Study with the TSP.- The Role of Syntactic and Semantic Locality of Crossover in Genetic Programming.- The Layered Learning Method and Its Application to Generation of Evaluation Functions for the Game of Checkers.

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Descriere

We are very pleased to present to you this LNCS volume, the proceedings of the 11th International Conference on Parallel Problem Solving from Nature (PPSN 2010). PPSN is one of the most respected and highly regarded c- ference series in evolutionary computation, and indeed in natural computation aswell.Thisbiennialeventwas'rstheldinDortmundin1990, andtheninBr- sels (1992), Jerusalem (1994), Berlin (1996), Amsterdam (1998), Paris (2000), Granada (2002), Birmingham (2004), Reykjavik (2006) and again in Dortmund in 2008. PPSN 2010 received 232 submissions. After an extensive peer review p- cess involving more than 180 reviewers, the program committee chairs went through all the review reports and ranked the papers according to the revi- ers comments. Each paper wasevaluated by at least three reviewers.Additional reviewers from the appropriate branches of science were invoked to review into disciplinary papers. The top 128 papers were ?nally selected for inclusion in the proceedings and presentation at the conference. This represents an acceptance rate of 55%, which guarantees that PPSN will continue to be one of the c- ferences of choice for bio-inspired computing and metaheuristics researchers all over the world who value the quality over the size of a conference. The papers included in the proceedingsvolumes covera wide range of topics, fromevolutionarycomputationto swarmintelligence, frombio-inspiredcomp- ing to real-world applications. Machine learning and mathematical games s- portedbyevolutionaryalgorithmsaswellasmemetic, agent-orientedsystemsare also represented. They all are the latest and best in natural computation. The proceedings are composed of two volumes divided into nine thematic sections."