Wave Planning
Orders grouped into waves that respect SLAs and minimise travel.
Wave Planning turns an order pool into a pick programme. Orders are grouped into waves that never violate an SLA cutoff, stay within labour and zone capacity, and overlap their pick locations so travel per line collapses.
~20%
travel reduction vs first-come-first-served
published batching benchmarks
0
waves that span an SLA cutoff
Releasing orders first-come-first-served is the most expensive default in fulfilment. Order batching is a genuinely hard optimisation problem — NP-hard beyond trivial sizes — which is why Awarehouse uses purpose-built heuristics refined against real operations: SLA-first bucketing, seed-and-grow clustering on pick-location overlap, and controlled order-splitting policies. Published benchmarks put well-designed batching around 20% travel reduction versus first-come-first-served; that is the design floor we engineer against.
Every wave is priced before release: estimated travel metres, labour minutes and SLA risk per wave. Waves at risk are flagged with the orders that put them there. Downstream, the plan feeds pick tasks straight into Task Manager and replenishment demand into Replenishment — one decision, three coordinated plans.
How it works
Wave Planning, in three moves.
01
Bucket
Orders split by SLA cutoff first. Deadlines are constraints, not suggestions.
02
Cluster
Within each bucket, orders that share aisles and zones grow into waves under labour and line caps.
03
Price & release
Each wave carries its travel and labour estimate. Release with confidence — downstream plans update automatically.
Capabilities
- SLA-cutoff bucketing — a wave never spans a shipping deadline
- Seed-and-grow clustering on aisle and zone overlap to compress travel
- Caps per wave: lines, orders, labour minutes and zones touched
- Order-splitting policy control: atomic orders never split
- Per-wave travel and labour estimates on real layout geometry
- SLA-risk flags with the offending orders identified