Drop-and-pull container drayage with flexible assignment of work break for vehicle drivers - Wang, Decheng; Zhang, Ruiyou; Qiu, Bin; Chen, Wenpeng; Xie, Xiaolan (Computers & operations research, 2024)
•A drop-and-pull container drayage with flexible work break is addressed.•A mixed-integer programming model is constructed to formulate this problem.•Three families of valid inequalities are proposed to strengthen the model.•A model-based backtracking adaptive threshold accepting algorithm is developed.•Managerial insights are presented on the work break. Consideration of driver-related constraints, such as mandatory work break, in vehicle scheduling and routing is of extraordinary importance for safety driving and guaranteeing the interests of vehicle drivers. Drop-and-pull transportation is an efficient mode in container drayage services and creates interdependencies between the routes of vehicle drivers. The situation becomes even more complicated when the drivers must comply with requirements of the mandatory work break. This paper addresses a drop-and-pull container drayage problem with flexible assignment of work break. The time and location of work break for drivers can be flexibly chosen based on scheduling, routing and optimization requirements. The transportation vehicle is comprised of two parts as a tractor and a trailer. The tractor can drag at most one trailer at a time, and is separable from the trailer when executing drayage activities. The problem is formulated as a mixed-integer programming model, which is then strengthened by proposing several families of valid inequalities. To efficiently solve realistic-sized instances, a backtracking adaptive threshold accepting algorithm with a mixed-integer programming model specially coping with the assignment of work break is proposed. Mechanisms of tabu search are incorporated to enhance the searching ability of the algorithm. Experiments indicate that the proposed algorithm can efficiently handle the vehicle scheduling and routing as well as the work break assignment and outperforms the mathematical programming approach. Sensitivity analyses about different policies and varied length of the work break are also conducted with some managerial insights presented.