https://github.com/poltanek/crane-random-search
Skeleton code for a simulation of a problem similar to the Crane problem however, implementing using random search algorithm expending random nodes
https://github.com/poltanek/crane-random-search
numpy python python3 random-search-algorithm
Last synced: 11 months ago
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Skeleton code for a simulation of a problem similar to the Crane problem however, implementing using random search algorithm expending random nodes
- Host: GitHub
- URL: https://github.com/poltanek/crane-random-search
- Owner: Poltanek
- License: mit
- Created: 2025-01-28T11:13:54.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-28T12:38:40.000Z (about 1 year ago)
- Last Synced: 2025-01-28T13:46:44.011Z (about 1 year ago)
- Topics: numpy, python, python3, random-search-algorithm
- Homepage:
- Size: 2.93 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Crane Simulation Project
## Table of Contents
- [Introduction](#introduction)
- [Key Components](#key-components)
- [Initial State](#initial-state)
- [State Visualisation](#state-visualisation)
- [Actions and Costs](#actions-and-costs)
- [Functionality](#functionality)
- [Performing Actions](#performing-actions)
- [Performing Action Sequences](#performing-action-sequences)
- [Examples](#examples)
- [Example 1: Move Right](#example-1-move-right)
- [Example 2: Move Right and Drop](#example-2-move-right-and-drop)
- [Example 3: Complex Sequence](#example-3-complex-sequence)
- [Applications](#applications)
- [Future Improvements](#future-improvements)
---
## Introduction
The **Crane Simulation Project** models the operation of a crane managing containers in a set of storage bays. The crane can move between bays, pick up containers, and drop them, while tracking the total operational cost. This project provides a foundation for simulating and optimizing warehouse or shipping yard operations.
---
## Key Components
### Initial State
- **`initial_bays`**: Represents storage bays as a list of lists. Each sublist contains the IDs of containers in a specific bay. Example:
```python
initial_bays = [[1, 2], [], [4], []]