Heuristics for Optimization and Learning

Inbunden, Engelska, 2020

Del i serien Studies in Computational Intelligence

1 787 kr

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Beskrivning

This book is a new contribution aiming to give some last research findings in the field of optimization and computing. 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.

Produktinformation

Utgivningsdatum:2020-12-16
Mått:155 x 235 x 31 mm
Vikt:852 g
Format:Inbunden
Språk:Engelska
Serie:Studies in Computational Intelligence
Antal sidor:442
Upplaga:20001
Förlag:Springer Nature Switzerland AG
ISBN:9783030589295

Utforska kategorier

Optimering inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT

Innehållsförteckning

Process Plan Generation for Reconﬁgurable 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-Efﬁcient 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 (α,β)-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 Classiﬁcation.- 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 Coefﬁcients 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.