Advance Shipment Reservation Problem

Abstract

This project addresses the challenges faced by companies that rely on outsourced carriers to ship goods to their customer: securing cost-effective, reliable capacity for on-time pickups. Without their own delivery fleets, these companies depend on contracted carriers to ensure competitive shipping rates for specific lanes. However, these contracts lack guaranteed capacity, as carriers serve multiple shippers and allocate capacity on a first-come, first-served basis. When capacity is fully utilized, shippers face two costly choices: sourcing higher-priced services from alternative carriers or the spot market, or risking delays that impact operational schedules and customer satisfaction. To reduce the likelihood of last-minute spot purchases, the shipper has to make advance capacity reservations. However, this strategy is complicated by demand uncertainty, as shippers must reserve space for orders that may not yet be finalized.This study develops a data-driven optimization model to establish an effective reservation policy, addressing uncertainties in carrier capacity and shipment demand. By leveraging historical data on demand patterns, carrier capacity, and rate fluctuations, the model suggests reservation quantities based on available information. It is designed to adapt as new information on demand and capacity becomes available, allowing the reservation policy to dynamically respond to changing conditions. This approach minimizes expected shipping costs while reducing the risk of capacity shortages and delays in scheduled pickups, providing companies with a flexible and responsive framework for managing outsourced shipping effectively.