Empirical Juridical Digital-Demand-Aggregation with Multi-Objective Optimization for Real-Time Quality-Hygiene Compliance and Cross-City Routing of Perishable Foods in Pesisir Barat

Background: The coastal province of Pesisir Barat depends on numerous small-to-medium enterprises that move highly perishable seafood and tropical fruits under fragmented demand, stringent food-safety statutes, and volatile maritime conditions. Objectives: To devise an integrated decision-support framework that simultaneously optimises vehicle routing, curtails product spoilage, and operationalises legal compliance for real-time cold-chain management. Methods: A rolling-horizon mixed-integer linear programming (MILP) model was built with decision variables for route selection (x_{ij}^{k,t}), load quantities (y_{ij}^{k,t}), and temperature state (T_i). The objective function aggregates transportation cost, a freshness index derived from an Arrhenius-based spoilage model, and regulatory penalty costs stipulated in the Indonesian Civil Code (KUHPerdata) and PMK No. 82/2012. Real-time IoT telemetry (temperature sampled each minute) and consumer-app demand forecasts update the model every 15 minutes. Contractual clauses translate temperature breaches (exceeding 4 degC for exceeding 120 min) and force-majeure triggers (BMKG sea-state ≥ 2.5 m, cyclone alerts) into enforceable penalties and arbitration under BANI. Results: On a 30-day dataset comprising 1,200 legs, the framework lowered average spoilage from 12.4 % to 5.8 % and cut total logistics cost by 7.3 % versus a static routing baseline. Sensitivity analysis confirmed robustness to demand-forecast errors up to +/-15 % and to fuel-price fluctuations of +/-10 %. Published in Journal of Coastal Frontiers and Applied Development (JCFAD). CERN Zenodo Record: https://doi.org/10.5281/zenodo.24088481. Publisher: PT CHAIN ASIA CONECT Research and Development Division.