INTERNATIONAL JOURNAL OF ADVANCE RESEARCH
IN MULTIDISCIPLINARY

The increasing complexity of logistics networks requires simultaneous consideration of transportation capacity, warehouse capacity, operational efficiency, and environmental sustainability. Conventional logistics planning approaches frequently optimize transportation and warehousing decisions independently, which can result in capacity imbalance, unnecessary transportation movements, warehouse congestion, and increased carbon emissions. This study proposes a multi-objective decision framework for integrated transport and warehouse capacity allocation under operational and environmental constraints. The proposed framework jointly determines transportation capacity allocation, warehouse utilization, shipment assignment, inventory flow, and vehicle movement while considering transportation cost, warehouse operating cost, capacity utilization, delivery requirements, and carbon emissions. A multi-objective mixed-integer optimization model is formulated to minimize total logistics cost and environmental impact while maximizing capacity utilization and maintaining required service levels. Operational constraints include vehicle capacity, warehouse storage limits, shipment demand, delivery requirements, inventory balance, transportation availability, and warehouse handling capacity. Environmental constraints incorporate vehicle-related emissions and warehouse energy consumption. The model generates a set of Pareto-optimal solutions representing different trade-offs between economic efficiency, operational performance, and environmental sustainability. A scenario-based evaluation is proposed to examine the effects of demand variation, transportation capacity limitations, warehouse capacity constraints, and emission restrictions. The framework provides an integrated decision-support mechanism for logistics managers to allocate limited transport and warehouse resources while maintaining service requirements and controlling environmental impacts.