This research examines the synergistic effects in logistics processes, using formal mathematical models. The models are based on queueing theory, network theory, and fuzzy compromise programming. The focus is on quantifying the benefits arising from the coordinated action of resources, technologies, and service channels. Through three analyzed case studies (simultaneous vehicle loading, logistics nodes, and intermodal transport), it is demonstrated that the application of synergy leads to a reduction in operation time in logistics by up to 52%, a reduction in the number of communication networks by up to 62%, a decrease in costs by up to 43%, and a shortening of delivery time by up to 45% through the introduction of intermediaries. In intermodal transport, significant cost optimization was also achieved. The developed models serve as a powerful tool for strategic decision-making, enabling the verification of synergistic effects in real logistics processes. The results unequivocally confirm that synergy is a practically applicable strategy for optimizing complex systems.