How Zalando accelerates warehouse operations with neural networks - Calvin Seward, Data Scientist at...

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  • How Zalando Accelerates Warehouse Operations with Neural

    Networks

    Calvin SewardBig Data Berlin v. 6.0

    28 January 2016

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  • Outline

    I Picker Routing Problem

    I Order Batching Problem

    I Neural Network Estimate of Pick Route Length

    I Order Batch optimization via Simulated Annealing

    This was a project that was a collaboration between Rolland Vollgraf, Sebastian Heinzand myself. Some of the gures have been shamelessly stolen from Roland.

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  • Outline

    I Picker Routing Problem

    I Order Batching Problem

    I Neural Network Estimate of Pick Route Length

    I Order Batch optimization via Simulated Annealing

    This was a project that was a collaboration between Rolland Vollgraf, Sebastian Heinzand myself. Some of the gures have been shamelessly stolen from Roland.

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  • Zalando's Logistics Centers

    I 13.8 Million orders from 01.07.15 30.09.15

    I 174,684 orders send per working day (Mo. Sa.)

    I Every second handling time per order requires 160 man-days of work / month

    I Any increase in ecency has a big impact

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  • Picker Routing ProblemThe locations that must be visited

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  • Picker Routing ProblemThe locations that must be visited

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  • Picker Routing ProblemThe Pick Route

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  • Picker Routing ProblemThe Pick Route

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  • Picker Routing ProblemThe Pick Route

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  • Picker Routing ProblemThe Pick Route

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  • Picker Routing ProblemThe Pick Route

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  • Picker Routing ProblemThe Pick Route

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  • OCaPi AlgorithmOptimal CArt PIck

    I To solve picker routing problem, wedeveloped the OCaPi Algorithm

    I Calculates the optimal route to walk

    I Also determines optimal cart handlingstrategy

    I Has complexity that is linear in thenumber of aisles

    I Unfortunately still has a runtime ofaround 1 second

    Figure: The Okapi Our Mascot

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  • OCaPi AlgorithmOptimal CArt PIck

    I To solve picker routing problem, wedeveloped the OCaPi Algorithm

    I Calculates the optimal route to walk

    I Also determines optimal cart handlingstrategy

    I Has complexity that is linear in thenumber of aisles

    I Unfortunately still has a runtime ofaround 1 second

    Figure: The Okapi Our Mascot

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  • OCaPi AlgorithmOptimal CArt PIck

    I To solve picker routing problem, wedeveloped the OCaPi Algorithm

    I Calculates the optimal route to walk

    I Also determines optimal cart handlingstrategy

    I Has complexity that is linear in thenumber of aisles

    I Unfortunately still has a runtime ofaround 1 second Figure: The Okapi Our Mascot

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  • Simplied Order Batching ProblemBipartite Graph Formulation

    n Orders

    o1

    o2

    o3

    . . .

    on

    m Pick Tours

    t1

    t2

    . . .

    tm

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  • Simplied Order Batching ProblemBipartite Graph Formulation

    n Orders

    o1

    o2

    o3

    . . .

    on

    m Pick Tours

    t1

    t2

    . . .

    tm

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  • Simplied Order Batching ProblemBipartite Graph Formulation

    n Orders

    o1

    o2

    o3

    . . .

    on

    m Pick Tours

    t1

    t2

    . . .

    tm

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  • Order Batching ProblemRandom Split of 10 Orders 2 Items Into Two Pick Routes

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  • Order Batching ProblemBrute Force Split of 10 Orders 2 Items into Optimal Two Pick Routes 8.3% Boost

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  • Neural Network Estimate of Pick Route Length

    I This simple example could be donewith brute force

    I A realistic example with 40 orders 2items has a complexity of

    40!

    2 20! 20! 6.9 1010

    at 1 second per route, you'd wait 2185years

    I Use clever heuristics like simulatedannealing

    I Estimate pick route length with NeuralNetworks

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  • Neural Network Estimate of Pick Route Length

    I This simple example could be donewith brute force

    I A realistic example with 40 orders 2items has a complexity of

    40!

    2 20! 20! 6.9 1010

    at 1 second per route, you'd wait 2185years

    I Use clever heuristics like simulatedannealing

    I Estimate pick route length with NeuralNetworks

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  • Neural Network Estimate of Pick Route Length

    I OCaPi cost landscape

    f : (N R)n R+

    is a nice function because it is:I Lipschitz continuous in the real-valued

    argumentsI Piecewise linear in the real-valued argumentsI Locally sensitive

    I Perfect function to model with ConvolutionalNeural Networks with ReLUs:

    f (x) := (W2(W1x + b1)+ + b2)+

    I Train convolutional neural network with 1million examples

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  • Neural Network Estimate of Pick Route Length

    I OCaPi cost landscape

    f : (N R)n R+

    is a nice function because it is:I Lipschitz continuous in the real-valued

    argumentsI Piecewise linear in the real-valued argumentsI Locally sensitive

    I Perfect function to model with ConvolutionalNeural Networks with ReLUs:

    f (x) := (W2(W1x + b1)+ + b2)+

    I Train convolutional neural network with 1million examples

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  • Neural Network Estimate of Pick Route LengthEstimation Accuracy Frequency of relative estimation error estimated travel time

    calculated travel time

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  • Neural Network Estimate of Pick Route LengthEstimation Speed Time Per Route on two Intel Xeon E5-2640 and two NVIDIA Tesla K80 accelerators

    number pick lists OCaPi CPU network GPU network

    1 5.369 2.202e-3 1.656e-310 1.326 1.991e-4 1.832e-4100 0.365 6.548e-5 5.919e-51000 3.086e-5 2.961e-510000 2.554e-5 2.336e-5

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  • Order Batch optimization via Simulated AnnealingEstimated and Exact Improvement in Example Simulated Annealing Run

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  • Questions?

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  • Thanks for listening

    Get The Slides Ongithub.com/cseward/ocapi_neural_net_blog_post

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