Abstract: This paper aims to reduce the probability of stevedores suffering from musculoskeletal diseases due to repeated bending during the cargo loading process, optimize their work posture comfort to reduce work fatigue, and thus improve the overall benefits of society. Based on the perspective of co-optimization of human factors engineering and operational research, we propose and study the vehicle loading problem that consider working posture comfort from the perspective of comfortable postures for stevedores. Firstly, the comfort of the loading work posture is evaluated to establish the model. Secondly, key issues such as cargo sorting optimization and cargo placement rules are studied. An algorithm combining the maximal-space heuristics and biased random-key genetic algorithm is designed. Finally, experimental verification is conducted through instances. Results show that the proposed model and algorithm can improve the comfort of stevedores' work postures without increasing vehicle transportation cost, Moreover, there is a greater optimization space of the work posture comfort for cargoes with relatively small sizes and scales, verifying the effectiveness of the model and algorithm.

Key words: three-dimensional bin packing, working posture comfort, maximal-space heuristics, biased random-key genetic algorithm