Warehouse Simulation with SimPy: From Receiving to Shipping

Published on February 21, 2026

Warehouses are logistics engines. Goods flow in, get stored, get picked, and flow out. Simulation reveals the bottlenecks between receive and ship. <h2 id="the-warehouse-model">The Warehouse Model</h2> Key processes: - Receiving - Goods arrive - Putaway - Storage in locations - Storage - Inventory holding - Picking - Order fulfillment - Packing - Preparation for shipping - Shipping - Goods leave <h2 id="basic-warehouse">Basic Warehouse</h2> <div class="code-block"><pre><code>import simpy import random class Warehouse: def __init__(self, env, config): self.env = env self.receiving_docks = simpy.Resource(env, capacity=config['receiving_docks']) self.forklifts = simpy.Resource(env, capacity=config['forklifts']) self.pickers = simpy.Resource(env, capacity=config['pickers']) self.packing_stations = simpy.Resource(env, capacity=config['packing_stations']) self.shipping_docks = simpy.Resource(env, capacity=config['shipping_docks']) self.inventory = simpy.Container(env, capacity=config['storage_capacity'], init=config['initial_inventory']) self.stats = {'received': 0, 'shipped': 0, 'orders': []} def receive_shipment(self, shipment_id, quantity): """Process incoming shipment.""" arrival = self.env.now # Dock with self.receiving_docks.request() as dock: yield dock yield self.env.timeout(random.uniform(15, 30)) # Unload # Putaway with forklift with self.forklifts.request() as forklift: yield forklift yield self.env.timeout(quantity * 0.5) # Time per pallet yield self.inventory.put(quantity) self.stats['received'] += quantity def process_order(self, order_id, items): """Pick, pack, and ship an order.""" order_start = self.env.now record = {'id': order_id, 'items': items, 'start': order_start} # Pick items with self.pickers.request() as picker: yield picker # Travel and pick time pick_time = sum(random.uniform(0.5, 2) for _ in range(items)) yield self.env.timeout(pick_time) yield self.inventory.get(items) record['picked'] = self.env.now # Pack with self.packing_stations.request() as station: yield station yield self.env.timeout(random.uniform(2, 5)) record['packed'] = self.env.now # Ship with self.shipping_docks.request() as dock: yield dock yield self.env.timeout(random.uniform(1, 3)) record['shipped'] = self.env.now record['total_time'] = self.env.now - order_start self.stats['orders'].append(record) self.stats['shipped'] += items # Run simulation env = simpy.Environment() warehouse = Warehouse(env, { 'receiving_docks': 3, 'forklifts': 5, 'pickers': 10, 'packing_stations': 6, 'shipping_docks': 4, 'storage_capacity': 10000, 'initial_inventory': 5000 }) </code></pre></div> <h2 id="zone-based-picking">Zone-Based Picking</h2> <div class="code-block"><pre><code>class ZonedWarehouse: def __init__(self, env, zone_config): self.env = env self.zones = {} for zone_name, config in zone_config.items(): self.zones[zone_name] = { 'inventory': simpy.Container(env, capacity=config['capacity'], init=config['initial']), 'pickers': simpy.Resource(env, capacity=config['pickers']) } def pick_order(self, order_id, items_by_zone): """Pick items from multiple zones.""" picked_items = [] for zone_name, items in items_by_zone.items(): zone = self.zones[zone_name] with zone['pickers'].request() as picker: yield picker yield zone['inventory'].get(items) pick_time = items * random.uniform(0.3, 0.8) yield self.env.timeout(pick_time) picked_items.extend([zone_name] * items) return picked_items # Zone configuration zone_config = { 'A': {'capacity': 3000, 'initial': 2000, 'pickers': 4}, # Fast movers 'B': {'capacity': 5000, 'initial': 3000, 'pickers': 3}, # Medium 'C': {'capacity': 8000, 'initial': 5000, 'pickers': 2}, # Slow movers } </code></pre></div> <h2 id="wave-planning">Wave Planning</h2> <div class="code-block"><pre><code>class WaveBasedWarehouse: def __init__(self, env, config): self.env = env self.config = config self.order_queue = simpy.Store(env) self.pickers = simpy.Resource(env, capacity=config['pickers']) self.waves_completed = 0 def receive_order(self, order): yield self.order_queue.put(order) def run_waves(self, wave_interval, orders_per_wave): """Release orders in waves.""" while True: yield self.env.timeout(wave_interval) # Collect orders for this wave wave_orders = [] while len(wave_orders) < orders_per_wave: try: order = yield self.order_queue.get() wave_orders.append(order) except: break if wave_orders: # Process wave yield self.env.process(self.process_wave(wave_orders)) self.waves_completed += 1 def process_wave(self, orders): """Process all orders in a wave.""" # Sort by zone to minimize travel orders.sort(key=lambda o: o.get('zone', 'A')) for order in orders: self.env.process(self.pick_order(order)) # Wait for all picks to complete yield self.env.timeout(0) </code></pre></div> <h2 id="conveyor-system">Conveyor System</h2> <div class="code-block"><pre><code>class ConveyorSystem: def __init__(self, env, speed, length): self.env = env self.speed = speed # Items per minute self.length = length # Sections self.sections = [simpy.Store(env, capacity=10) for _ in range(length)] def put_item(self, item): """Put item on conveyor at start.""" yield self.sections[0].put(item) def run(self): """Move items along conveyor.""" while True: yield self.env.timeout(1 / self.speed) # Move items from end to start for i in range(self.length - 1, 0, -1): if self.sections[i-1].items: item = yield self.sections[i-1].get() yield self.sections[i].put(item) def get_item(self): """Get item from end of conveyor.""" return self.sections[-1].get() </code></pre></div> <h2 id="complete-warehouse-simulation">Complete Warehouse Simulation</h2> <div class="code-block"><pre><code>import simpy import random import numpy as np class FullWarehouseSimulation: def __init__(self, env, config): self.env = env self.config = config # Resources self.receiving = simpy.Resource(env, capacity=config['receiving_docks']) self.putaway_crew = simpy.Resource(env, capacity=config['putaway_workers']) self.inventory = simpy.Container(env, capacity=config['storage'], init=config['initial_stock']) self.pickers = simpy.Resource(env, capacity=config['pickers']) self.packers = simpy.Resource(env, capacity=config['packers']) self.shipping = simpy.Resource(env, capacity=config['shipping_docks']) # Stats self.order_stats = [] self.inbound_stats = [] def inbound_shipment(self, shipment_id, pallets): """Process inbound delivery.""" arrival = self.env.now record = {'id': shipment_id, 'pallets': pallets, 'arrival': arrival} # Receive with self.receiving.request() as dock: yield dock unload_time = pallets * random.uniform(2, 4) yield self.env.timeout(unload_time) record['unloaded'] = self.env.now # Putaway with self.putaway_crew.request() as worker: yield worker putaway_time = pallets * random.uniform(3, 6) yield self.env.timeout(putaway_time) yield self.inventory.put(pallets * 50) # 50 units per pallet record['stored'] = self.env.now record['total_time'] = self.env.now - arrival self.inbound_stats.append(record) def outbound_order(self, order_id, units): """Process customer order.""" arrival = self.env.now record = {'id': order_id, 'units': units, 'arrival': arrival} # Wait for inventory if needed yield self.inventory.get(units) record['allocated'] = self.env.now # Pick with self.pickers.request() as picker: yield picker lines = max(1, units // 5) pick_time = lines * random.uniform(1, 3) yield self.env.timeout(pick_time) record['picked'] = self.env.now # Pack with self.packers.request() as packer: yield packer pack_time = random.uniform(2, 5) yield self.env.timeout(pack_time) record['packed'] = self.env.now # Ship with self.shipping.request() as dock: yield dock yield self.env.timeout(random.uniform(1, 3)) record['shipped'] = self.env.now record['total_time'] = self.env.now - arrival self.order_stats.append(record) def inbound_arrivals(self): """Generate inbound deliveries.""" shipment_id = 0 while True: yield self.env.timeout(random.expovariate(self.config['inbound_rate'])) pallets = random.randint(10, 30) self.env.process(self.inbound_shipment(shipment_id, pallets)) shipment_id += 1 def order_arrivals(self): """Generate customer orders.""" order_id = 0 while True: # Time-varying order rate hour = (self.env.now / 60) % 24 if 9 <= hour <= 17: rate = self.config['peak_order_rate'] else: rate = self.config['off_peak_order_rate'] yield self.env.timeout(random.expovariate(rate)) units = random.randint(5, 50) self.env.process(self.outbound_order(order_id, units)) order_id += 1 def inventory_monitor(self, interval=60): """Track inventory levels.""" self.inventory_log = [] while True: self.inventory_log.append({ 'time': self.env.now, 'level': self.inventory.level }) yield self.env.timeout(interval) def run(self, duration): self.env.process(self.inbound_arrivals()) self.env.process(self.order_arrivals()) self.env.process(self.inventory_monitor()) self.env.run(until=duration) def report(self): print("\n=== Warehouse Simulation Report ===") print(f"Duration: {self.env.now / 60:.1f} hours") print(f"\nInbound:") print(f" Shipments: {len(self.inbound_stats)}") if self.inbound_stats: times = [s['total_time'] for s in self.inbound_stats] print(f" Avg dock-to-stock: {np.mean(times):.1f} min") print(f"\nOutbound:") print(f" Orders: {len(self.order_stats)}") if self.order_stats: times = [s['total_time'] for s in self.order_stats] print(f" Avg order cycle time: {np.mean(times):.1f} min") print(f" 90th percentile: {np.percentile(times, 90):.1f} min") print(f"\nInventory:") levels = [l['level'] for l in self.inventory_log] print(f" Avg level: {np.mean(levels):.0f} units") print(f" Min level: {min(levels):.0f} units") # Config config = { 'receiving_docks': 3, 'putaway_workers': 4, 'storage': 50000, 'initial_stock': 25000, 'pickers': 12, 'packers': 6, 'shipping_docks': 4, 'inbound_rate': 0.02, 'peak_order_rate': 0.5, 'off_peak_order_rate': 0.1 } random.seed(42) env = simpy.Environment() sim = FullWarehouseSimulation(env, config) sim.run(duration=480) # 8 hours sim.report() </code></pre></div> <h2 id="summary">Summary</h2> Warehouse simulation captures: - Inbound and outbound flows - Resource constraints (docks, workers, equipment) - Inventory dynamics - Order cycle times - Zone-based operations Simulate before you build. Optimise before you fail. <h2 id="next-steps">Next Steps</h2> <ul> <li><a href="/blog_posts/simpy-supply-chain-simulation.html">Supply Chain Simulation</a></li> <li><a href="/blog_posts/simpy-manufacturing-simulation.html">Manufacturing Simulation</a></li> <li><a href="/blog_posts/simpy-container-explained.html">Container Explained</a></li> </ul>

Build Professional Simulations

Break free from commercial software and learn how to build powerful, industry-standard simulations in Python. The Complete Simulation in Python with SimPy Bootcamp gives you everything you need.

Explore the Bootcamp