A speed and departure time optimization algorithm for the Pollution-Routing Problem

TL;DR

This paper introduces a quadratic-time algorithm for optimizing speed and departure times in the Pollution-Routing Problem, integrated into a metaheuristic to improve operational efficiency and cost savings.

Contribution

It presents a novel quadratic-time algorithm for PRP that optimizes speed and departure times, enhancing routing and scheduling efficiency.

Findings

Operational costs reduced by 8.36% on benchmark instances.

Algorithm achieves certified optimal schedules efficiently.

Flexible departure times improve route profitability and resource allocation.

Abstract

We propose a new speed and departure time optimization algorithm for the Pollution-Routing Problem (PRP), which runs in quadratic time and returns a certified optimal schedule. This algorithm is embedded into an iterated local search-based metaheuristic to achieve a combined speed, scheduling and routing optimization. The start of the working day is set as a decision variable for individual routes, thus enabling a better assignment of human resources to required demands. Some routes that were evaluated as unprofitable can now appear as viable candidates later in the day, leading to a larger search space and further opportunities of distance optimization via better service consolidation. Extensive computational experiments on available PRP benchmark instances demonstrate the good performance of the algorithms. The flexible departure times from the depot contribute to reduce the operational costs by 8.36% on the considered instances.