A multi-trip freight macro-consolidation routing model with hybrid GRASP-ALNS-DJO optimisation algorithm: a case study of Portsmouth, UK

This study explores the potential sustainability impacts (economic, environmental, social) of introducing a Macro Consolidation Centre (MCC) on the outskirts of Portsmouth, as part of the Solent Future Transport Zone (FTZ) project funded by the UK’s Department for Transport. The freight distribution problem is modelled as a Multi-Trip Capacitated Vehicle Routing Problem with Time Constraints (MCVRPT).

A metaheuristic approach, referred to as GRASP-ALNS-DJO algorithm, is developed by integrating the Greedy Randomised Adaptive Search Procedure (GRASP), Adaptive Large Neighborhood Search (ALNS) and the Discrete Jaya Optimisation algorithm (DJO). GRASP algorithm is used to generate an initial solution, then this solution is improved using ALNS with adaptive selection of destruction and repair operators.

Finally, an enhanced DJO algorithm is applied which incorporates routebased crossover, adaptive perturbation and diversity-preserving mechanisms.

This paper presents a case study on the impact of implementing an MCC in the city of Portsmouth. Preliminary computational experiments were conducted by solving benchmark instances of the CVRP from the literature and comparing the results with those of a recent efficient algorithm, in order to demonstrate the applicability of the proposed approach and provide initial insights into its potential sustainability benefits.