Logistics

Logistics connects global supply chains, ensuring goods move efficiently from production to consumption. Effective logistics management focuses on transportation planning, routing, fleet utilization, and cost optimization, while also considering sustainability and resilience.

Supply Chain Network Design

  • Multi-period supply chain network design (SCND) problem

SCND — Multi-Period Network Design (NL, 2026–2030)

Strategic timing & siting of FCs to balance transport OPEX vs. FC CAPEX & Ops across all half-years.

1) Why It Matters

Opening FCs closer to demand reduces Hub→FC and FC→DC haul lengths, but adds CAPEX and FC Ops. The best plan changes as topline grows over time.

  • Too few FCs → high transport OPEX, possible shortfalls.
  • Too many/early → CAPEX & Ops overhead before needed.
Goal: Choose where and when to open 10k–25k FCs so total cost over 2026H1–2030H2 is minimized while meeting demand.
Half-year periods Capacity bands Nearest-FC routing

2) Compact Formulation

\[ \begin{align} \min\;\; & \sum_{f\in F}\sum_{k\in K} \mathrm{CAPEX}_{f,k}\, y_{f,k} + \sum_{t\in T}\Big(\mathrm{OPEX}^{\mathrm{trans}}_t + \mathrm{OPEX}^{\mathrm{ops}}_t\Big) \tag{1} \end{align} \]
\[ \begin{align} \mathrm{OPEX}^{\mathrm{trans}}_t &= \frac{\mathrm{days}_t}{10^6}\Big[ \alpha \Big(\sum_{h,f} x^{HF}_{t,h,f} + \sum_{f,d} x^{FD}_{t,f,d}\Big) + r \Big(\sum_{h,f} d^{HF}_{h,f}\, x^{HF}_{t,h,f} + \sum_{f,d} d^{FD}_{f,d}\, x^{FD}_{t,f,d}\Big) \Big] \\ \mathrm{OPEX}^{\mathrm{ops}}_t &= \sum_{f\in F} \mathrm{OpsYear}_{k(f)} \cdot \frac{\mathrm{days}_t}{365}\, z_{f,t} \tag{2} \end{align} \]
\[ \begin{align} q_{t,d} &= \mathrm{Topline}_t \cdot s_d, \quad s_d=\sum_{h\in H} s_{h,d}, \quad \sum_{d\in D} s_d \approx 1 \\ 500\sum_{f} x^{FD}_{t,f,d} &\ge q_{t,d} && \forall t,d \\ 500\sum_{h} x^{HF}_{t,h,f} &\ge 500\sum_{d} x^{FD}_{t,f,d} && \forall t,f \\ 500\sum_{d} x^{FD}_{t,f,d} &\le \mathrm{cap}_{k(f)}\, z_{f,t} && \forall t,f \\ z_{f,t} &= 1 \ \text{iff}\ t\ge \text{start}(f), \qquad y_{f,k}\in\{0,1\},\ \sum_{k} y_{f,k}\le 1 \tag{3} \end{align} \]

\(x^{HF}\) and \(x^{FD}\) are trucks (not orders, capacity = 500 orders/truck); \(\alpha=50\) €/truck and \(r=1.5\) €/km. The allocator uses nearest-FC assignment under capacity; costs follow (1)–(3) across all periods.

3) Data & Assumptions

  • Topline per period (daily), exact days per half-year (leap-aware).
  • Hub→DC share matrix → DC demand split.
  • Fixed distances (km): Hub→FC and FC→DC; trucks handle 500 orders.
  • FC CAPEX by city/band; yearly FC Ops by band; one-off CAPEX upon opening.

4) References

Try It

Open the planner and toggle FC openings to see capacity sufficiency and total-cost impact across all periods.

Open SCND demo
Nuxt + Tailwind + Chart.js; greedy DC→FC allocator with capacity and multi-period OPEX aggregation.