Muutke küpsiste eelistusi

Heuristics for Optimization and Learning 2021 ed. [Kõva köide]

Edited by , Edited by , Edited by
  • Formaat: Hardback, 442 pages, kõrgus x laius: 235x155 mm, kaal: 852 g, 97 Illustrations, color; 71 Illustrations, black and white; XV, 442 p. 168 illus., 97 illus. in color., 1 Hardback
  • Sari: Studies in Computational Intelligence 906
  • Ilmumisaeg: 16-Dec-2020
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030589293
  • ISBN-13: 9783030589295
Teised raamatud teemal:
  • Kõva köide
  • Hind: 150,61 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Tavahind: 177,19 €
  • Säästad 15%
  • Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 2-4 nädalat
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Lisa soovinimekirja
Heuristics for Optimization and Learning 2021 ed.Suurem pilt
  • Formaat: Hardback, 442 pages, kõrgus x laius: 235x155 mm, kaal: 852 g, 97 Illustrations, color; 71 Illustrations, black and white; XV, 442 p. 168 illus., 97 illus. in color., 1 Hardback
  • Sari: Studies in Computational Intelligence 906
  • Ilmumisaeg: 16-Dec-2020
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030589293
  • ISBN-13: 9783030589295
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783030589295.html
This book is a new contribution aiming to give some last research findings in the field of optimization and computing. This work is in the same field target than our two previous books published: Recent Developments in Metaheuristics and Metaheuristics for Production Systems, books in Springer Series in Operations Research/Computer Science Interfaces.





The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications. 





The number of researches dealing with decision maker tool and optimization method grows very quickly these last years and in a large number of fields. We may be able to read nice and worthy works from research developed in chemical, mechanical, computing, automotive and many other fields.
Process Plan Generation for Recongurable Manufacturing Systems: Exact
vs Evolutionary-Based Multi-Objective Approaches.- On VNS-GRASP and Iterated
Greedy Metaheuristics for Solving Hybrid Flow Shop Scheduling Problem with
Uniform Parallel Machines and Sequence Independent Setup Time.- A Variable
Block Insertion Heuristic for the Energy-Efcient Permutation Flowshop
Scheduling with Makespan Criterion.- Solving 0-1 Bi-Objective
Multi-Dimensional Knapsack Problems using Binary Genetic Algorithm.- An
asynchronous parallel evolutionary algorithm for solving large .instances of
the multi-objective QAP.- Learning from Prior Designs for Facility Layout
Optimization.- Single-objective Real-parameter Optimization: Enhanced
LSHADE-SPACMA Algorithm.- Operations Research at Bulk Terminal: A Parallel
Column Generation Approach.- Heuristic solutions for the (,)-k feature set
problem.- Generic Support for Precomputation-Based Global Routing Constraints
in Local Search Optimization.- Dynamic Simulated Annealing with Adaptive
Neighborhood using Hidden Markov Model.- Hybridization of the differential
evolution algorithm for continuous multi-objective optimization.- A
Steganographic Embedding Scheme Using Improved-PSO Approach.- Algorithms
towards the Automated Customer Inquiry Classication.-  An heuristic scheme
for a reaction advection diffusion equation.- Stock Market Speculation System
Development based on Technico Temporal indicators and Data Mining Tools.- A
New Hidden Markov Model Approach for Pheromone Level Exponent Adaptation in
Ant Colony System.- A new cut-based genetic algorithm for graph partitioning
applied to cell formation.-  Memetic algorithm and evolutionary operators for
multi-objective matrix tri-factorization problem.- Quaternion simulated
annealing.- A Cooperative Multi-Swarm Particle Swarm Optimizer Based Hidden
Markov Model.- Experimental Sensitivity Analysis of Grid-Based Parameter
Adaptation Method.-  Auto-Scaling System in Apache Spark Cluster using
Model-Based Deep Reinforcement Learning.- Innovation Networks from
Inter-Organizational Research Collaborations.- Assessing Film Coefcients of
Microchannel Heat Sinks via Cuckoo Search Algorithm.- One-Class Subject
Authentication using Feature Extraction by Grammatical Evolution on
Accelerometer Data.- Semantic composition of word-embeddings with genetic
programming.- New Approach for Continuous and Discrete Optimization:
Optimization by Morphological Filters.