Territory Planning and Logistics Network Optimization
For supply chains with significant multi-stop delivery routes, traditional supply chain design and territory planning tools and models often produce highly inaccurate results. Traditional supply chain network tools do not directly model multi-stop routes and schedules (including stop sequences, time windows, driver workloads, truck types, etc.), and instead roll up shipments to point-to-point “flows” of quantities. In contrast, the Sci-Log solution automatically evaluates the precise impact, costs, miles volumes, and driver headcount of different supply chain configurations and strategies on multi-stop routes. The centralized design and use of parallel computing within the Sci-Log solution also make it easy to analyze and optimize a multi-stop distribution system across an entire enterprise, allowing enormous national supply chains to be modeled and efficiently analyzed. Sci-Log produces rapid automated results even on models with thousands of trucks and hundreds of facilities or more.
Sci-Log can also be used to optimize hub-and-spoke network configurations which contain fundamental differences compared to traditional logistics network systems. Optimized hub-and-spoke networks generally feature highly asymmetric or skewed territories to prevent delivery trucks from “doubling-back” too much towards distribution centers or parent spokes.
Routing Strategies and What-if Simulations
Firms with truck fleets face ongoing higher-level routing questions and decisions, such as the impact of new business on existing routes, how to tradeoff customer service windows with transportation cost, the impact of driver overtime policies, etc. Traditional routing systems do not provide much help with these analyses, as each scenario must be interactively analyzed and solved, a tedious and time-consuming process. The Sci-Log solution automatically generates high quality route plans, making routing strategy analyses practical and fast. The Sci-Log solution also maintains a centralized data warehouse of historical orders and routes across multiple facilities or distribution centers, so histories can be automatically “played back” to evaluate the impact of different business rules or costs.