Some solutions for specific cases

Solutions

Linear Optimization

1. Invention of intensity modulated radiation therapy (IMRT)
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2. Maximize revenue
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3. Price and Demand Optimization
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Integer Optimization

1. Scheduling
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Spatial Optimization

1. Location Optimization Using Weighted Parameters
   • Street network isochrones
   • Population Density (35%)
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   • Accessibility weighted (25%)
   • Coverage gaps (15%)
   • Constain areas - Competitor (25% if absence)
2. Real World Facility Location Problem
   • Location Set Covering Problem (LSCP)
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   • Maximal Coverage Location Problem (MCLP)
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   • P-Center Problem
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   • P-Median Problem
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Propensity / churn / CLTV

1. Buy Till You Die (BTYD) Models
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2. Behavioral & Sequence-Based Models
   • RFM + ML classifier
   • RFM scoring
3. Survival Analysis
   • Time-to-Event Models
   • Hazard Models
4. Machine Learning
5. Deep Learning
6. Hybrid & Business-Oriented Models
   • Rule-Based + ML Hybrid
   • Customer Scoring Systems
7. Markov Chain Models
8. Causal & Uplift Models
9. Cross-sales Models
   • Next-product-to-buy algorithms

Recommendation system

1. Classic algorithms
   • Baseline
   • NormalPredictor
   • SVD and SVD++ algorithm
   • Non-negative Matrix Factorization
   • Stochastic Gradient Descent (SGD)
   • Weighted Alternating Least Squares (WALS)
   • SlopeOne algorithm
   • WARP (Weighted Approximate-Rank Pairwise)
   • BPR (Bayesian Personalized Ranking)
2. Machine Learning
   • Classification models
   • Logistic regression
   • Logistic matrix factorization
   • SVM
   • Tree based model
   • Ensemble model
   • LightGBM / XGBoost
   • Clustering techniques
   • K-means clustering
   • Co-clustering
3. Deep Learning
   • Neural Collaborative Filtering
   • Wide & Deep
   • Two-Tower Models (User tower + Item tower)
   • Transformer-based session models
4. Graph-Recommendation Engine model
   • Graph-based recommender
5. Learning-to-Rank Models
   • LambdaMART
   • RankNet
   • XGBoost ranking
   • LightGBM ranking

Demand-Supply (Supply Chain)

1. Optimizing Supply and Demand Matchmaking (Weight Scoring)
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2. Optimization Problem
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3. Route-based combinatorial optimization problems
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Inventory and warehouse

1. ABC analysis

Segmentation

1. Clustering
   • CentNN
   • K-means
   • K-modes
   • MK-means
   • K-prototypes
   • C-means
   • SOM and minisom
   • clarans
   • Affinity Propagation
   • Mean Shift
   • Spectral Clustering
   • Agglomerative Clustering
   • DBSCAN
   • OPTICS
   • Birch
   • Spectral Co-clustering
   • Spectral Bi-clustering
   • Gaussian Mixture
   • Gaussian HMM
   • Hierarchical Clustering
2. RFM (recency, frequency, monetary)
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3. Hyperpersonalized marketing campaigns

Marketing budget allocation

Marketing strategic

1. Online learning - Thompson Sampling

Fraud detection

Scoring

1. Linear Regression
2. Beta weight

Credit Scoring

1. Scoring type A
   • Rule based
   • Scorecard
   • Machine learning
   • Deep Learning
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Spatial Analysis

1. Spatial hypotesis and autocorrelation Analysis
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2. Heatmap Distribution
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Data collection

1. Scraping data
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Prediction (binary or multiclass)

1. Logistic Regression
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Regression

Time Series

Distance Measurement

1. Spatial Distance Metrics
   1. Manhattan Distance
   2. Euclidean Distance
   3. Chebyshev Distance
   4. Minkowski Distance
   5. Mahalanobis Distance
   6. Minimum-Maximum Coordinate Distance
   7. Centroid Distance
2. Vector Similarity Metrics
   1. Cosine Similarity
   2. Jaccard Similarity
   3. Sorensen-Dice Coefficient
   4. Levenshtein Distance (Edit Distance)
   5. Hamming Distance

Computer Vision

1. Image Classification
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2. Object Detection
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3. Semantic Segmentation / Pixel Classification
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4. Instance Segmentation / Object Segmentation
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5. Panoptic Segmentation
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6. Change Detection
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7. Image Translation
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8. Object Tracker
9. Image Captioning