As logistics and supply chains (SC) deal a priori with physical movement of produced materials and products (transportation, warehousing, trans-shipment and order-picking processes, i.e., logistics) and integration and coordination of these processes with each other and with the transformation production processes (i.e., supply chain management SCM), dynamics exists both in logistics systems and in SCs inevitably. Understanding the importance and the impact of dynamics on performance and resilience of logistics and SC systems is becoming a more and more important topic in literature and in practice [6, 7, 17, 29, 30, 48]. As modern logistics and SC systems are highly networked, integrated, and coordinated, the conventionally isolated problems of operations and logistics management evolve into networked problems, which are characterized by multi-dimensional characteristics (e.g., multi-stage, multi-period, multi-commodity, etc.) [4, 39, 44]. The existence of a great diversity of different dynamic characteristics in those problems, e.g., demand fluctuations, inventory dynamics, dynamic lot-sizes, dynamic schedules, changes in suppliers structures, information dynamics subject to partial or full information unavailability, natural and human-driven catastrophes and attacks on logistics and SC systems can significantly impact logistics and SC performance [7, 17, 48]. The distribution of these dynamic characteristics upon different structures (organizational, functional, product-based, informational, financial, etc.) along with the coordinated and distributed decision-making (so called active decision makers, unlike in automatic systems) subject to the above-mentioned multidimensional space lead to the understanding of modern logistics and SC systems as multi-structural active systems with structure dynamics [21, 27]
