Article
Publicly Available
Frontmatter
Published/Copyright:
March 30, 2019
Published Online: 2019-03-30
Published in Print: 2019-04-24
©2019 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Elite Opposition-Based Cognitive Behavior Optimization Algorithm for Global Optimization
- Preventive Maintenance Optimization and Comparison of Genetic Algorithm Models in a Series–Parallel Multi-State System
- An Improved Correlation Coefficient of Intuitionistic Fuzzy Sets
- Evaluation of Flexible Manufacturing Systems Using a Hesitant Group Decision Making Approach
- Analysis of the Use of Background Distribution for Naive Bayes Classifiers
- Fully Automated Segmentation of Lung Parenchyma Using Break and Repair Strategy
- Segmentation of Brain Tumour Based on Clustering Technique: Performance Analysis
- Interval-Valued Intuitionistic Fuzzy Confidence Intervals
- An Optimized Face Recognition System Using Cuckoo Search
- A Bi-objective Genetic Algorithm Optimization of Chaos-DNA Based Hybrid Approach
- Iterated Local Search for Time-extended Multi-robot Task Allocation with Spatio-temporal and Capacity Constraints
Articles in the same Issue
- Frontmatter
- Elite Opposition-Based Cognitive Behavior Optimization Algorithm for Global Optimization
- Preventive Maintenance Optimization and Comparison of Genetic Algorithm Models in a Series–Parallel Multi-State System
- An Improved Correlation Coefficient of Intuitionistic Fuzzy Sets
- Evaluation of Flexible Manufacturing Systems Using a Hesitant Group Decision Making Approach
- Analysis of the Use of Background Distribution for Naive Bayes Classifiers
- Fully Automated Segmentation of Lung Parenchyma Using Break and Repair Strategy
- Segmentation of Brain Tumour Based on Clustering Technique: Performance Analysis
- Interval-Valued Intuitionistic Fuzzy Confidence Intervals
- An Optimized Face Recognition System Using Cuckoo Search
- A Bi-objective Genetic Algorithm Optimization of Chaos-DNA Based Hybrid Approach
- Iterated Local Search for Time-extended Multi-robot Task Allocation with Spatio-temporal and Capacity Constraints