A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem

Full truckload transportation (FTL) in the form of freight containers represents one most important modes international trade. Due to large volume and scale, FTL, delivery time is often less critical but cost service quality are crucial. Therefore, efficiently solving scale multiple shift FTL problems becoming more requires further research. In our earlier studies, a set covering model three-stage solution method were developed for multi-shift problem. This paper extends previous work presents significantly efficient approach by hybridising pricing cutting strategies with metaheuristics (a variable neighbourhood search genetic algorithm). The adopted find promising columns (vehicle routes) guided cuts dynamically generated eliminate infeasible flow assignments caused incompatible commodities. Computational experiments on real-life artificial benchmark showed superior performance both terms computational quality, when compared MIP based methods two existing metaheuristics. proposed heuristic can solve problems.