KERANGKA DINAMIS PENGAMBILAN KEPUTUSAN MULTI-KRITERIA PADA OPTIMASI RUTE KENDARAAN CAMPURAN TERTUTUP-TERBUKA BERBASIS KEBERLANJUTAN UNTUK JARINGAN PENGIRIMAN JARAK MENENGAH

This repository constitutes the complete open-science replication package for the research paper:  
> *"A Dynamic Multi-Criteria Decision-Making Framework for Sustainable Close-Open Mixed Vehicle Routing Problem in Middle-Mile Logistics (DCOAHTOP)"*

The dataset and software encompass:
1. **Empirical Historical Logistics Dataset (`Dataset/dbpos.sql`)**: 19,850 historical delivery transactions and routing matrices across 13 Distribution Centers (DCs) coordinated by the Postal Processing Center (PPC) Bandung 40400, PT Pos Indonesia.
2. **Replication Scripts & Metaheuristics Algorithms**:
   - Adaptive Genetic Algorithm (AGA) with dynamic self-tuning operator rates and MCDM-seeded chromosomes.
   - Comparative baselines: Standard Genetic Algorithm (SGA), Tabu Search (TS), Ant Colony Optimization (ACO), and Static MCDM-COMVRP.
   - Simulation engines implemented in Python, Node.js, and standalone client-side JavaScript.
3. **Multi-Objective Benchmark & Experimental Results (`Tables/`)**:
   - Raw carbon emission simulation data across 30 replications (150 runs, 5 algorithms) calibrated to empirical vehicle specifications (`table17_carbon_raw.csv`).
   - Comprehensive multi-objective evaluation tables (Distance, Carbon Emissions, Hypervolume, Generational Distance, Solomon VRPTW benchmark deviations, and Wilcoxon signed-rank tests).
4. **Interactive Web-Based Research Dashboard (`index.html`)**: Interactive GIS network visualization, real-time AHP-TOPSIS engine, AGA convergence viewer, and publication analytics.