The 3D Bin Packing problem is a classic combinatorial optimization problem that has wide applications in logistics, warehousing, transportation, and many other fields. Its core is to reasonably pack a series of three-dimensional items (boxes) of various sizes into a limited number of three-dimensional containers (boxes, cargo containers, etc.), with the typical goal of minimizing the number of containers used or maximizing the utilization rate of containers while satisfying various constraints.

Enhance your data generation with MockHero's Schema Aware Data Generation API, ensuring data integrity and relevance.

The Synthetic Data Synthetic Data MockHero API allows developers to generate diverse datasets while preserving privacy and compliance.

MockHero’s Mock Data API simplifies creating placeholder data, perfect for testing and development needs.

Validate structured data markup on any web page including JSON-LD, Microdata, and RDFa. Detects Schema.org types, checks for errors, and returns detailed validation results.

Extract structured tables from PDF files and return them as JSON, Excel, or CSV. Automatically detects single or multiple tables, supports multi-page PDFs, and delivers deterministic, machine-readable output for data pipelines and automation.

Access comprehensive data on the world’s tallest structures effortlessly with this API.

Use the Database Seeding Database Seeding MockHero API to populate your databases with quality test data, streamlining your development workflow.

Access worldwide domain data effortlessly with the SEO Structure Checker API for informed decisions.

Extract structured data from documents with high-accuracy OCR, including personal details, dates, numbers, and formatted text for verification and automation.

Effortlessly generate dynamic test data on demand using MockHero's Dynamic Test Data API, optimizing your testing process.

Create fully customizable fake data quickly using MockHero's Fake Data API, tailored to your project’s requirements.

Extracts and validates JSON-LD, Microdata, RDFa, and structured markup from webpages or raw HTML for SEO and technical validation.

Your ultimate solution for reducing memory usage, cutting storage costs, and enhancing application performance—all without the need to rewrite your existing business logic. With a single API call, you receive a comprehensive savings report detailing the optimization in bytes, KB, MB, or GB.

Streamline your workflows with our Document Data Extraction API, designed to transform any structured or unstructured document into actionable, structured data.

The Hockey Database API provides structured access to historical and current hockey statistics, team records, and more. It allows users to retrieve data efficiently by filtering through various categories and teams.

Extract structured GS1 application identifiers from machine-readable or human-readable barcodes with high accuracy and field-level metadata.

Effortlessly extract and digitize critical information from documents with our Document Data Capture API.

Unlock valuable insights by scraping content from various document formats with the Document Content Scraper API.

Seamlessly convert scanned documents into editable text using the Extract Text from Documents API.

Text Classification API is a tool for organizing unstructured text data into predefined categories. It uses machine learning algorithms to analyze and categorize text data, making it easier to organize and understand.

Effortlessly extract structured data such as names, emails, amounts, and dates from plain text using our AI Data Extraction API. Experience rapid, flexible, and user-friendly data processing tailored to meet your needs.

Convert recipe URLs into AI-structured data. Extract ingredients, instructions, names, descriptions, images and more for culinary applications or recipe management.

Simplify content manipulation with an API designed to extract clean text or markdown from any web page.

Deliver structured smart city performance data by country and city.