YvesNDIKURIYO-2022/En-NSGA-II-4-LC-CTRP
Domain:
mobilityenvironment and energyCreator:
Yve
Host:
Enhanced NSGA-II framework for low-carbon container transportation routing on the Mombasa-Bujumbura corridor. Achieves 68% lower emissions than NSGA-II at 10% cost premium. Identifies $55/ton as optimal carbon price with 48.8% decarbonization potential.
# Multi-Objective Optimization of Low-Carbon Container Routing Using PA-NSGA-II
**Python** • **MIT License** • **Paper** • **Data**
A Parameter-Adaptive NSGA-II Framework for Low-Carbon Container Routing on the Mombasa–Bujumbura Corridor.
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## Overview
This repository contains the complete code, data, and analysis for the paper:
> **"A Parameter-Adaptive Multi-Objective Evolutionary Algorithm for Low-Carbon Container Routing under Uncertainty"**
>
> *Yves Ndikuriyo, Yinggui Zhang, Dung Davou Fom*
>
> *School of Traffic and Transportation Engineering, Central South University, Changsha, China*
>
> *Computational Optimization and Applications (Under Review)*
### What is LC-CTRP?
The **Low-Carbon Container Transportation Routing Problem (LC-CTRP)** optimizes multimodal freight routes, balancing three conflicting objectives:
| Objective | Description | Unit |
|-----------|-------------|------|
| **Cost** | Total transportation + transshipment + carbon costs | USD |
| **Emissions** | CO₂ emissions from road, rail, and waterway transport | kg CO₂ |
| **Time** | Total transit time including border delays and transshipment | hours |
### What is PA-NSGA-II?
The **Parameter-Adaptive NSGA-II (PA-NSGA-II)** is a hybrid multi-objective optimization framework that integrates:
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ PA-NSGA-II Framework │
├─────────────────────────────────────────────────────────────────────────────┤
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Adaptive │───▶│ Size- │───▶│ NSGA-II │ │
│ │ PPO │ │ Adaptive │ │ Pareto │ │
│ │ Initialization│ │ Config. │ │ Search │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
└────────────────────────────────────────────────────── …