Data & Intelligence Global One Team ‘Optimization’ › english › optimization.pdf ·...

© 2019 NTT DATA Mathematical Systems Inc.

15 Feb. 2019NTT DATA Mathematical Systems, Inc.Takahito Tanabe ([email protected])

Data & Intelligence Global One Team

NTT DATA Mathematical Systems, Inc. ‘Optimization’

2© 2019 NTT DATA Mathematical Systems Inc.

1.What is Optimization • Control & Constraint

2.Examples• Production Planning ( maxworkload .vs. inventry)

• Production Planning ( costly equipment )

• Cutting Stock

• Stock Allocation

3.Optimization project in Reality• Our Standpoint

• Manager & Practitioner

• Driver Required!

• Let’s PoC together

‘Optimization’ : NTT Data Mathematical Systems, Inc.


What is Optimization ?


Maximize compatibility (objective) under matching constraint

Constrained Recommendation

Job ApplicantCompany

Typical Recommendation

Job ApplicantCompany

ConstrainedRecommendation

#applicants ≧ N (∝ pay)for each Company


What is Mathematical Optimization ?

Find the optimal CONTROL or DECISIONthat satisfies CONSTRAINTS


Examples


Production management (Orders with various due date)


Production management (Orders with various due date)

When to produce ?


Production planning : Balance workload ?

Control the production date to balance the machine load

workload (no control)

days


Production planning : Constrain the workload

workload(optimized)

days

max workloadconstraint

Production was pushed forward according to optimization result.


Production planning : Inventory minimized

Inventory cost

days

minimized


Greedy strategy tested with Our Simulation Tool S4

Push forward all the production to the workload limit !With various inventory maximum (parameter)


Simulation and Optimization

Simulation results

optimizationresults

max workload

inventorycost

max workload / cost

Inventory cost and max workload are offset


Production Resource Planning at a Japanese Manufacturer (2013-)

You can control the product flow

Each product requires certain machine resources we should allocate

Each machine needs costly special equipment to handle each product’s process

Reduce equipment keeping the production output within the available machine resource

product A

product flow of B

product flow of A

machineproduct B

Achievement: Reduced special equipments by 30～50%# of machines : 60

# of products : 48


A Cutting Stock Problem for Film Manufacturer (2017-)

Cutting Patterns Example

width of ‘1’ width of ‘2’

fixed size

pattern ‘1’ pattern ‘2’

…

Determine Cutting Pattern (2D region tiled by rectangular products) Product requirement constrained Reduce (# of Cutting Pattern) ⇔ (amount of loss)

loss


Data Maintenance Schedule for IT company (2018-)

Assign Data maintenance/counting task (#500) to either of 2 machines Due date / precedence / capacity constraint should be fulfilled.

precedence

capacity


Stock allocation

Control stock allocation for orders at {A,B,C,D} Allocate from neighbouring storage is cost-minimum Quality balance offsets shipping cost

1 1i

i

x =orderAmount

Dj D

j

x Stock

,

ij ij

i j

c x

storageA

storageB

storageC

order#1

order#2

storageDorder#6

order#3

order#7

……

…

Balancequality

mixed quality

Control Allocation


Stock allocation demo


Optimization in Reality


Solve real world problem for business practitioners

⇒ Our packaged softwares are ‘stock in trade’ for this purpose （Numerical Optimizer is one of them）

Our Standpoint

AcademiaBusiness

Practitioners MSI

Sponser

mathematicalmodels

Businessrequirements

algorithms

theories

software


‘Optimization’ everywhere ! (supply chain)

demand

feedstock

factory

warehouse/storage

customer

blend raw materials roster staffs select line for production allocate production resource manage storage for feedstock create cutting pattern

plan shipment

arrange (half-finished) goods

stock allocation loading

routing configuration assign route to vehicle


Managers and Practitioners

IT System Integrator

Practitioner#1

Practitioner#2

Practitioner#3

commitment!

our own ..

Fulfill ..

managerial personnel

Save Cost!

driven by

Constraintdriven by

Objective

GAP

cost,revenue,investment..

due-dateresource

regulation..


Traditionally in Japan ..

Practitioner#1

Practitioner#2

Practitioner#3

commitment!

our own ..

Fulfill ..

driven by

Constraint

due-dateresource

regulation..

untouchable


But ..

Practitioner#1

Practitioner#2

Practitioner#3

commitment!

our own ..

Fulfill ..

driven by

Constraint

due-dateresource

regulation..

untouchable

MathematicalOptimization

appeals!


Mathematical Optimizaion promotes communication

IT System Integrator

Practitioner#1

Practitioner#2

Practitioner#3

commitment!

our own ..

Fulfill ..

managerial personnel

GO Digital

driven by

Constraintdriven by

Objective

Numerical Optimizer

cost,revenue,investment..

due-dateresource

regulation..


Collect Data ;Build Model ;Solve ;

Process of Mathematical Optimization


while (!satisfy(output)) {Collect Data ;Build Model ;Solve ;Examine Result;if ( budget? ) exit;

}

Process of Mathematical Optimization in Reality

Something is wrong with

this solution ..

I’ll fix it bymodifying the

model !

Trial & Error


Responsible Leader Required !

Who knows value of the final outcome

≠ data scientist

• Go to that goal !• What happened ? Now

choose plan B !


Aiming for Deploy …

CHASMline balancing

resource planning

routing

stockallocation

！

！

Our optimization engine is working in Domestic sites:

JR-stationChain StoreCall CenterProduction center Air conditioning …

EVERY DAY

optimization integrated system


Aiming for Deploy …

line balancing

resource planning

routing

stockallocation

！

！

Why don’t we start OptimizationProof of Concept

by applying it to your actual situations?

CHASM

optimization integrated system


We can also provide materials to introduce optimization

Data & Intelligence Global One Team ‘Optimization’ › english › optimization.pdf ·...

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