Multicriteria Optimization of A Long-Haul Routing and Scheduling Problem

Long‐haul carriers are facing a shortage of drivers in North American countries. To reduce turnover rates and improve driver retention, trucking companies are making more efforts to improve their drivers' quality of life. The aim of this paper is to introduce and solve a multi‐objective vehicle routing and truck driver scheduling problem under the legislative requirements on work and rest hours in the US (US MOVRTDSP). We present a tabu search algorithm that solves the US MOVRTDSP and provides a heuristic non‐dominated solution set from which tradeoffs between operating costs and driver inconvenience are evaluated. The tradeoffs between the number of vehicles used and operating costs are also estimated. Overall, interpretations of the computational results on artificial and real‐life instances provide meaningful information to long‐haul carriers.