Trade-offs in ready-mixed concrete truck scheduling considering stochastic congestion: A novel multi-objective model driven by strength Pareto evolutionary algorithm

Abstract

Ready-mixed concrete (RMC) is extensively used in the construction industry due to its high quality and efficiency. However, as market competition intensifies, RMC companies are under increasing pressure to improve their competitiveness while maintaining strong customer relationships. Efficiently dispatching trucks and optimizing RMC delivery to meet both customer demands and company needs has become a significant challenge for RMC companies’ development. To this end, this study first conducts a demand analysis of RMC truck scheduling from both supply and demand perspectives and identifies five key scheduling objectives: operational cost, load rate, load balancing, time windows, and continuity of concrete pouring. Secondly, objective dimensionality reduction is achieved by constructing composite load and penalty functions and integrating a congestion time function to simulate traffic congestion scenarios. On this basis, a tri-objective optimization model that balances total cost, composite load, and customer satisfaction is constructed, which reduces the complexity of model computation without compromising the integrity of objective constraints. Then, the study innovatively designs decision variables for truck numbers and departure intervals and employs the strength Pareto evolutionary algorithm based on reference direction (SPEA/R) to solve the model. Additionally, the mutation operation was improved by introducing traffic congestion variables and dynamically adjusting departure intervals to mitigate the impact of congestion on scheduling. This facilitates the refinement of RMC truck scheduling in terms of both truck configuration and dispatch planning under traffic congestion conditions. Finally, a Chinese RMC company case study was conducted to validate the effectiveness of the proposed model. Based on the findings, a two-dimensional RMC truck scheduling strategy matrix was developed, offering diverse guidance and recommendations for RMC factories to formulate truck scheduling plans that meet varying demands.