YvesNDIKURIYO-2022/En-MOEA-D-Container-Routing

Official implementation of Enhanced MOEA/D (En-MOEA/D) for multi-objective robust container routing. Features adaptive decomposition, Monte Carlo simulation, mean-variance risk control. Includes ZDT/DTLZ/WFG benchmarks, robust test problems, and East African case study. Associated with Applied Soft Computing paper. # En-MOEA/D: Enhanced Multi-Objective Evolutionary Algorithm based on Decomposition for Container Routing under Uncertainty **Preprint:** DOI: 10.2139/ssrn.5399005 **Official implementation of the Enhanced MOEA/D (En-MOEA/D) algorithm** for multi-objective robust optimization of container routing problems under uncertainty. This repository contains all the code necessary to reproduce the experiments and results presented in the paper: > *"A Multi-objective Robust Optimization based on Evolutionary Algorithm for container routing problems under risks and uncertainties"* (Applied Soft Computing, 2026) **Authors:** Yves Ndikuriyo, Yinggui Zhang, Dung Davou Fom **Corresponding author:** Yves Ndikuriyo (yvesndikuriyo@csu.edu.cn) **Institution:** School of Traffic and Transportation Engineering, Central South University, Changsha, China --- ## 📋 Table of Contents - Overview - Key Innovations - Performance Highlights - Repository Structure - Installation - Running Experiments - Configuration - Output and Visualization - Authors - Citation - License - Acknowledgments --- ## 📋 Overview En-MOEA/D is a novel framework that bridges the critical gap between multi-objective optimization and robust decision-making for container routing under uncertainty. The algorithm integrates three key innovations to explicitly balance expected performance, worst-case resilience, and operational stability. The framework has been extensively validated on: - **ZDT, DTLZ, and WFG benchmark suites** - Demonstrating superior convergence and diversity - **Robust test problems** - GFunction, Ishigami, OakleyOHagan, and more - **Real-world East African logistics network** - Northern and Central Corridors connecting landlocked countries to maritime ports --- ## 🔬 Key Innovations ### 1. Adaptive Decomposition Mechanism Dynamically transitions between PBI (Penalty Boundary Intersection) and Chebyshev scalarization based on search progress: - **Early stages**: PBI maximizes solution diversit …