... SimWell extracted data from multiple databases, including manual inputs and electronic databases. The tool structured information and prepared it for use in anyLogistix. Read also: To learn about data integration, read our blog on building a digital twin with anyLogistix API. Custom constraints The consultants addressed unique business constraints using Big M and mathematical formulations in anyLogistix. The Big M method is a linear programming technique for handling constraints ...

... of agility is planning for different scenarios. With approaches like simulation , companies can test out “what if” situations—like a supplier going offline or a sudden demand spike—and see how their supply chain responds . Technologies like digital twins, AI, and optimization engines help make this possible. A digital twin is a virtual version of a real supply chain, where you can run tests without risking real-world disruption. Discover more in our blog post → Collaboration tools can also help ...

... reduce their carbon footprint but also minimize supply chain costs. INNOVATIVE APPROACHES FOR GREEN SUPPLY CHAIN MANAGEMENT Innovative technologies and policies are shaping the future of transportation planning in supply chain management. For example, digital twins enable companies to create virtual replicas of their supply chains, allowing for better monitoring, prediction, and optimization of operations that bring benefits of green supply chain management. Meanwhile, easier ways for CO2 emission calculation ...

Vea cómo anyLogistix ayuda a optimizar su cadena de suministro mediante la simulación y el modelado de gemelos digitales. Diapositivas de la presentación (PDF) Vea cómo anyLogistix ayuda a optimizar su cadena de suministro mediante la simulación y el modelado de gemelos digitales. Este seminario web presenta la interfaz y los casos de uso del software. Agenda: ¿Qué es el modelado de simulación? ¿Qué desafíos puede resolver usando la simulación? Demos: Greenfield Analysis (GFA) Network Optimization...

... Singapore-based SupChainEra with determining a feasible distribution network design that would ensure high network performance compliant with corporate standards in terms of inventory and service levels. The consulting team from SupChainEra needed to build a digital twin of the current network, and then use the base model for logistics and planning optimization purposes. As the simulated network was extensive, accounting for 20,000 sites within the modeled region of South East Asia, and included multiple tiers, ...