In logistics and supply chain management, cross-docking operations play a pivotal role in enhancing efficiency and reducing storage costs. This study introduces an innovative multi-objective integer programming model aimed at minimizing total operation time and reducing internal transportation costs within cross-docking facilities. By integrating environmental considerations, the research seeks to reduce carbon emissions and operational costs, addressing the urgent need for sustainable logistics practices. Our solution approach adapts the SA algorithm to the unique context of cross-docking, involving a dynamic and complex coordination of inbound and outbound trucks. We meticulously tailored the cooling schedule, as well as acceptance probabilities to suit the intricate nature of logistics operations. The findings offer significant insights into applying these optimization techniques to real world scenarios, promising substantial improvements in logistical operations' environmental and economic performance.
Omar et al. (2024) studied this question.