Atlas Logo

Getting Started

  • Introduction to Atlas
    • Executive Summary
    • Why Atlas?
    • Core Philosophy
      • 1. Model Agnostic Architecture
      • 2. Business-First Design
      • 3. Enterprise-Ready Standards
      • 4. Open and Extensible
    • Key Capabilities
      • Unified Model Integration
      • Advanced Optimization Engine
      • Multi-Dimensional Data Management
      • Business Intelligence Integration
    • Target Users
    • Business Value Proposition
    • Getting Started
    • Framework Architecture
    • Next Steps
  • Quick Start Guide
    • Prerequisites
    • Installation
      • Install from PyPI
      • Install from Source
    • Your First Optimization
      • Step 1: Import Required Components
      • Step 2: Create a Simple Model
      • Step 3: Define Optimization Constraints
      • Step 4: Run Optimization
      • Expected Output
    • Real-World Example: Multi-KPI Optimization
    • Using Docker Models
    • Advanced Features Quick Examples
      • 1. Scenario Analysis
      • 2. Real-Time Optimization
      • 3. Model Registry Usage
    • Configuration Management
    • Next Steps
    • Getting Help
    • Common Issues
      • Issue: ImportError
      • Issue: Model Not Found
      • Issue: Optimization Not Converging

Core Concepts

  • 4 Core Concepts
    • Overview
    • Data
      • Data Architecture
      • Core Data Structures
        • Budget Allocations
        • Model Outputs
        • Historical Data
      • Data Operations
        • Budget Aggregation
        • Data Alignment
        • Resampling and Interpolation
      • Data Validation
      • Data Transformation
        • Unit Conversion
        • Time Aggregation
        • Feature Engineering
      • Data Import/Export
        • File Formats
        • Database Connections
        • API Integration
      • Data Performance
        • Lazy Loading
        • Efficient Storage
    • Models
      • Model Types
        • Machine Learning Models
        • Statistical Models
        • External Services
        • Custom Models
      • Model Integration
        • 1. Direct Python Integration
        • 2. Docker Container Integration
        • 3. API Integration
      • Model Requirements
        • Required Methods
        • Optional Methods
      • Model Validation
    • Optimization
      • Optimization Backends
        • SciPy Optimizer
        • Optuna Optimizer
        • CVXPY Optimizer
      • Multi-Objective Optimization
      • Optimization Strategies
        • Single-Point Optimization
        • Multi-Start Optimization
        • Scenario Optimization
      • Performance Optimization
        • Caching
        • Parallel Execution
        • Warm Starting
    • Constraints
      • Constraint Types
        • Budget Constraints
        • Business Rule Constraints
        • Temporal Constraints
        • Performance Constraints
      • Custom Constraints
      • Constraint Validation
      • Constraint Relaxation
    • Integration Example
  • Data
    • Overview
    • Why Data Matters in Optimization
    • Key Concepts
      • Multi-Dimensional Nature
      • Data Sources and Integration
      • Data Quality and Validation
    • Real-World Applications
      • Marketing Mix Modeling
      • Hospital Resource Planning
      • Supply Chain Optimization
    • Benefits of Atlas’s Data Approach
      • Reduced Complexity
      • Improved Accuracy
      • Faster Insights
      • Enhanced Flexibility
    • Common Data Patterns
      • Time Series Alignment
      • Hierarchical Structures
      • Sparse Data
      • External Data Integration
    • Getting Started with Data
    • Best Practices
      • Start Simple
      • Document Everything
      • Validate Continuously
      • Plan for Growth
    • Next Steps
  • Models
    • Overview
    • Understanding Models in Optimization
    • The Power of Model Agnosticism
      • Why It Matters
      • Integration Without Disruption
    • Types of Models
      • Statistical Models
      • Machine Learning Models
      • Business Rule Models
      • Hybrid Approaches
    • Real-World Model Applications
      • Marketing Mix Modeling
      • Healthcare Capacity Planning
      • Supply Chain Optimization
      • Dynamic Pricing
    • Model Requirements in Atlas
      • Answer Prediction Queries
      • Handle Valid Inputs
      • Provide Timely Responses
      • Maintain Reliability
    • Model Validation and Trust
      • Why Validation Matters
      • Building Trust
    • Common Model Patterns
      • Diminishing Returns
      • Interaction Effects
      • Temporal Dynamics
      • Uncertainty Quantification
    • Getting Started with Models
      • For Business Users
      • For Technical Teams
    • The Future of Models in Atlas
    • Next Steps
  • Optimization
    • Overview
    • What is Optimization?
    • The Optimization Landscape
      • Different Problems, Different Approaches
      • Single vs. Multi-Objective
    • How Optimization Works
      • The Search Process
      • Intelligent Exploration
    • Real-World Optimization Scenarios
      • Marketing Budget Allocation
      • Healthcare Staff Scheduling
      • Supply Chain Network Design
      • Product Portfolio Optimization
    • Advanced Optimization Features
      • Pareto Frontier Analysis
      • Scenario Optimization
      • Rolling Horizon Optimization
      • Warm Starting
    • Optimization Performance
      • Speed Matters
      • Scalability
    • Making Optimization Accessible
      • For Business Users
      • For Technical Users
    • Common Optimization Patterns
      • Budget Allocation
      • Scheduling
      • Network Flow
      • Portfolio Selection
      • Capacity Planning
    • Getting Started with Optimization
      • Define Clear Objectives
      • Identify Decision Variables
      • Understand Constraints
      • Start Simple
      • Iterate and Refine
    • The Future of Optimization
    • Next Steps
  • Constraints
    • Overview
    • Why Constraints Matter
    • Understanding Constraints
      • Hard Constraints
      • Soft Constraints
      • Dynamic Constraints
    • Types of Business Constraints
      • Budget and Financial Constraints
      • Operational Constraints
      • Strategic Constraints
      • Regulatory and Compliance Constraints
    • Real-World Constraint Examples
      • Marketing Mix Optimization
      • Hospital Staff Scheduling
      • Supply Chain Planning
    • How Atlas Handles Constraints
      • Intelligent Validation
      • Constraint Prioritization
      • Adaptive Relaxation
    • Benefits of Proper Constraint Management
      • Risk Mitigation
      • Stakeholder Alignment
      • Practical Implementation
      • Continuous Improvement
    • Common Constraint Patterns
      • Mutual Exclusivity
      • Conditional Logic
      • Capacity Sharing
      • Time Dependencies
      • Balance Requirements
    • Designing Effective Constraints
      • Start with Business Logic
      • Be Specific but Flexible
      • Document Reasoning
      • Plan for Change
      • Test Thoroughly
    • Managing Constraint Complexity
      • Hierarchical Organization
      • Version Control
      • Performance Impact
    • The Future of Constraints
      • Intelligent Constraint Learning
      • Natural Language Constraints
      • Constraint Explanation
    • Getting Started with Constraints
    • Next Steps

Features

  • Atlas Features
    • Overview
    • Core Features
      • 1. Universal Model Integration
        • Supported Model Types
        • Integration Methods
      • 2. Multi-Objective Optimization
        • Key Capabilities
        • Supported Objectives
      • 3. Advanced Optimization Algorithms
        • SciPy Backend
        • Optuna Backend
        • CVXPY Backend
      • 4. Constraint Management
        • Constraint Types
      • 5. Multi-Dimensional Data Handling
        • Supported Dimensions
      • 6. Real-Time Optimization
        • Features
      • 7. Scenario Analysis & What-If Planning
        • Capabilities
      • 8. Model Registry & Version Control
        • Features
      • 9. Visualization & Reporting
        • Visualization Types
        • Report Generation
      • 10. API & Integration Ecosystem
        • REST API
        • Python SDK
        • Integrations
    • Advanced Features
      • Model Chaining & Nesting
      • Custom Optimization Strategies
      • Distributed Optimization
    • Performance & Scalability
    • Getting Started with Features

Design Guides

  • Black Box Model Integration Guide
    • Overview
    • Key Components
      • 1. BlackBoxModelConfig
      • 2. BlackBoxModelConfigBuilder
      • 3. BlackBoxModel
    • Quick Start Examples
      • Example 1: Simple Linear Model
      • Example 2: Marketing Mix Model with Saturation
      • Example 3: Multi-Geography Model with Constraints
    • Advanced Features
      • Custom Contribution Calculation
      • Preprocessing and Transformations
      • Working with Time Series
    • Integration with Atlas Optimization
      • Using with Different Optimizers
      • Multi-Objective Optimization
    • Best Practices
      • 1. Validate Your Functions
      • 2. Use Meaningful Variable Names
      • 3. Document Metadata
      • 4. Set Reasonable Bounds
      • 5. Save and Version Configurations
    • Troubleshooting
      • Common Issues
    • Next Steps
  • Model Integration Design Guide
    • Overview
    • Model Integration Principles
    • Integration Approaches
      • Approach 1: Direct Python Integration
        • Step 1: Implement the AbstractModel Interface
        • Step 2: Create Model Configuration
        • Step 3: Register and Test the Model
      • Approach 2: Docker Container Integration
        • Step 1: Create Model Service
        • Step 2: Create Dockerfile
        • Step 3: Create Docker Wrapper
      • Approach 3: External API Integration
        • Step 1: Create API Wrapper
    • Best Practices
      • 1. Input Validation
      • 2. Error Handling
      • 3. Performance Optimization
      • 4. Monitoring and Logging
      • 5. Testing Strategy
    • Model Lifecycle Management
      • Version Control
      • Model Registry Integration
    • Troubleshooting Guide
      • Common Issues and Solutions
    • Next Steps
  • Custom Optimization Strategy Guide
    • Overview
    • Business Problem - US Distribution Network Inventory Optimization
      • The Challenge
      • Business Objectives
    • Strategy Design
      • Core Components
      • Mathematical Framework
    • Implementation Guide
      • Step 1: Define the Strategy Interface
      • Step 2: Implement Core Optimization Logic
      • Step 3: Implement Demand Forecasting
      • Step 4: Optimize Base Stock Levels
      • Step 5: Optimize Network Transfers
      • Step 6: Handle Uncertainty and Risk
      • Step 7: Create Performance Monitoring
    • Integration with Atlas
      • Step 1: Register the Strategy
      • Step 2: Configure the Strategy
      • Step 3: Execute Optimization
    • Testing and Validation
      • Unit Testing
      • Integration Testing
      • Performance Testing
    • Deployment Considerations
      • Configuration Management
      • Monitoring and Alerts
      • Continuous Improvement
    • Results and Benefits
      • Expected Outcomes
      • Key Success Factors
    • Conclusion
  • Performance Tuning Guide
    • Table of Contents
    • Performance Profiling
      • Identifying Bottlenecks
      • Using Line Profiler
      • Memory Profiling
    • Model Optimization
      • Optimize Model Predictions
        • 1. Vectorized Operations
        • 2. Model Simplification
        • 3. Model Caching
      • Batch Processing
    • Optimizer Performance
      • Algorithm Selection
      • Optimizer Configuration
        • SciPy Optimization
        • Optuna Optimization
      • Early Stopping
    • Data Handling
      • Efficient Data Structures
        • Use Xarray Efficiently
        • Lazy Loading
      • Data Preprocessing
    • Parallel Processing
      • Multi-threaded Optimization
      • GPU Acceleration
      • Distributed Optimization
    • Caching Strategies
      • Multi-level Caching
      • Smart Cache Invalidation
    • Memory Management
      • Memory-Efficient Data Loading
      • Garbage Collection
      • Memory Monitoring
    • Infrastructure Optimization
      • Docker Optimization
      • Kubernetes Scaling
    • Monitoring and Benchmarking
      • Performance Metrics
      • Continuous Benchmarking
    • Best Practices Summary
      • Quick Wins
      • Architecture Patterns
      • Monitoring Checklist
    • Performance Troubleshooting
      • Common Issues and Solutions
      • Debug Performance Issues
  • Production Deployment Guide
    • Table of Contents
    • Pre-Deployment Checklist
      • Code Readiness
      • Infrastructure Requirements
      • Operational Readiness
    • Deployment Architectures
      • Single Server Deployment
      • Microservices Architecture
    • Docker Deployment
      • Production Dockerfile
      • Docker Compose Production
      • Production Nginx Configuration
    • Kubernetes Deployment
      • Deployment Manifest
      • Service and Ingress
      • Horizontal Pod Autoscaler
    • Cloud Deployments
      • AWS Deployment
        • ECS Task Definition
        • CloudFormation Template
      • Google Cloud Deployment
      • Azure Deployment
    • API Gateway Setup
      • Kong Configuration
    • Security Considerations
      • Security Checklist
      • Security Configuration
    • Monitoring and Observability
      • Prometheus Metrics
      • Logging Configuration
      • Grafana Dashboard
    • Backup and Recovery
      • Backup Strategy
      • Recovery Procedures
    • Troubleshooting Production Issues
      • Common Issues and Solutions
        • High Memory Usage
        • Slow Response Times
        • Database Connection Issues
      • Production Debugging
    • Post-Deployment
      • Health Checks
      • Smoke Tests
    • Maintenance
      • Rolling Updates
      • Maintenance Mode
  • Configuration Guide
    • Table of Contents
    • Configuration Overview
      • Configuration Loading Order
    • Configuration File Formats
      • YAML Configuration (Recommended)
      • JSON Configuration
      • TOML Configuration
    • Environment Variables
      • Standard Environment Variables
      • Loading Environment Variables
    • Model Configuration
      • Model Registry Configuration
      • Model-Specific Configuration
    • Optimizer Configuration
      • Optimizer Profiles
      • Dynamic Optimizer Selection
    • Constraint Configuration
      • Constraint Templates
      • Dynamic Constraints
    • Logging Configuration
      • Structured Logging
      • Log Aggregation
    • API Configuration
      • Rate Limiting Configuration
      • CORS Configuration
    • Performance Tuning
      • Cache Configuration
      • Worker Configuration
    • Best Practices
      • Configuration Management
      • Security Considerations
      • Configuration Testing

API Reference

  • Core Classes
    • Table of Contents
    • Models
      • AbstractModel
        • Class Definition
        • Methods
      • ModelWrapper
        • Class Definition
        • Example Usage
      • DockerModelWrapper
        • Class Definition
        • Methods
        • Example Usage
    • Optimizers
      • BaseOptimizer
        • Class Definition
      • ScipyOptimizer
        • Class Definition
        • Configuration Options
        • Example Usage
      • OptunaOptimizer
        • Class Definition
        • Configuration Options
        • Example Usage
    • Strategies
      • BaseOptimizationStrategy
        • Class Definition
      • MultiObjectiveStrategy
        • Class Definition
        • Example Usage
    • Configuration
      • ConfigurationManager
        • Class Definition
        • Example Usage
      • ModelConfiguration
        • Class Definition
    • Results
      • OptimizationResult
        • Class Definition
        • Properties and Methods
    • Utilities
      • Factory Classes
        • OptimizerFactory
        • ModelFactory
      • Data Utilities
        • BudgetConverter
        • ConstraintValidator
      • Visualization Utilities
        • OptimizationVisualizer
    • Error Handling
      • Custom Exceptions
    • Best Practices
      • 1. Model Integration
      • 2. Error Handling
      • 3. Configuration Management
    • Version Information

Examples

  • Marketing Mix Modeling (MMM) Example
    • Overview
    • Complete MMM Implementation
      • Step 1: Setup and Data Preparation
      • Step 2: Load and Prepare Marketing Data
      • Step 3: Create Marketing Mix Model
      • Step 4: Set Up Optimization
      • Step 5: Run Optimization for Different Scenarios
      • Step 6: Advanced Analysis
      • Step 7: Generate Executive Report
      • Step 8: Continuous Optimization
    • Key Takeaways
    • Next Steps
  • Scikit-learn Integration with Atlas
    • Overview
    • Installation
    • Quick Start
      • 1. Loading an Existing Model
      • 2. Using the Factory Pattern
      • 3. Configuration-Based Setup
    • Supported Models
      • Registering Custom Models
    • Feature Contributions
    • Working with Time Series
    • Best Practices
      • 1. Feature Scaling
      • 2. Model Validation
      • 3. Contribution Methods
    • Troubleshooting
      • Common Issues
    • Advanced Usage
      • Multi-Objective Optimization
      • Custom Preprocessing
    • Performance Tips
    • Next Steps

Additional Resources

  • Changelog
    • [0.0.1] - 2025-08-01
      • Added
      • Fixed
      • Changed
      • Deprecated
      • Removed
      • Security
  • Contributing to Atlas
    • Table of Contents
    • Code of Conduct
    • Getting Started
      • Types of Contributions
      • First-Time Contributors
    • Development Setup
      • Prerequisites
      • Setting Up Your Environment
      • Development Tools
    • Making Contributions
      • Finding Something to Work On
      • Workflow
      • Commit Message Convention
    • Coding Standards
      • Python Style Guide
      • Code Structure
      • Type Hints
      • Error Handling
    • Testing Guidelines
      • Test Structure
      • Writing Tests
      • Test Coverage
      • Integration Tests
    • Documentation
      • Docstring Format
      • Documentation Updates
      • Building Documentation
    • Pull Request Process
      • Before Submitting
      • PR Template
      • Review Process
      • After Merge
    • Community
      • Getting Help
      • Becoming a Maintainer
      • Recognition
    • Thank You!
  • Frequently Asked Questions (FAQ)
    • General Questions
      • What is Atlas?
      • Who should use Atlas?
      • How is this different from other optimization tools?
      • What are the system requirements?
    • Installation and Setup
      • How do I install the framework?
      • Can I use this with my existing models?
      • Do I need Docker?
      • How do I handle authentication for cloud models?
    • Model Integration
      • How do I integrate a scikit-learn model?
      • Can I use R models?
      • How do I handle models with preprocessing?
      • What about deep learning models?
    • Optimization
      • How do I choose the right optimizer?
      • Can I optimize over time periods?
      • How do I handle non-linear constraints?
      • What if optimization doesn’t converge?
    • Performance
      • How can I speed up optimization?
      • How much data can the framework handle?
      • Can I use GPU acceleration?
    • Deployment
      • How do I deploy to production?
      • How do I monitor optimization jobs?
      • Can I schedule regular optimizations?
    • Troubleshooting
      • Common Error Messages
        • “Model prediction shape mismatch”
        • “Constraint violation in optimal solution”
        • “Memory error during optimization”
      • How do I debug optimization issues?
    • Best Practices
      • Should I normalize my data?
      • How often should I retrain models?
      • What’s the best way to handle multiple currencies?
    • Advanced Topics
      • Can I implement custom optimization algorithms?
      • How do I handle uncertainty in predictions?
      • Can I use the framework for non-marketing applications?
    • Support
      • Where can I get help?
      • How do I report a bug?
      • Can I contribute to the project?
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    • Technical Acronyms
    • Mathematical Notation
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