Zero–one goal programming for multi-objective vehicle scheduling: coverage and cost optimization in flood relief logistics

Flood disasters in Kelantan, particularly in Pasir Mas, frequently disrupt transportation networks and create urgent demands for the timely distribution of relief supplies to Temporary Evacuation Centres (PPS). Relief operations face significant challenges, including limited vehicle availability, time pressure, and operational constraints, which in turn lead to inefficient vehicle scheduling and uneven service coverage. To address this issue, this study proposes a Zero–One Goal Programming (ZOGP) model to optimize assignment-based vehicle scheduling for flood relief distribution. The ZOGP framework incorporates multiple and conflicting objectives, namely, maximizing the number of PPS served, minimizing total travel distance and time, and minimizing transportation cost. The model employs binary variables for vehicle-to-PPS assignments and service status. LINGO optimization software is implemented with secondary data. Results demonstrate that the ZOGP model serves all selected PPS locations while satisfying all operational constraints. Overall, the proposed ZOGP model offers a practical and effective decision-support approach for enhancing flood relief vehicle scheduling.