ROSTUDEL OPTIMIZATION AS A SERVICE rostudel.com. OAAS (Optimization As A Service) OR : Theory + code (libraries+modelers) Architecture Consulting R&D.

ROSTUDEL

OPTIMIZATION AS A SERVICE

rostudel.com

OAAS (Optimization As A Service) OR : Theory + code

(libraries+modelers) Architecture Consulting R&D : Seminars, University

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OR CRISIS ?

4 success stories : we can actually use OR for realistic problems

OAAS can brand OR to Operational Resources, not only to a dedicated PHd Team

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1st Story : Scheduling People Retail organizations : employees, activities,

constraints, workload, daily patterns, week scope => timetable at a 15 minutes detail

LP to cover workload + BALAS to linearize disjunctions

Dynamic Programming + CP + dominacy rules to generate Shift

Branch and Price when final MIP isn’t enough

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Timetable

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2nd story : Smooth Cars Purchase with split batches. Balance holding cost and day demand

JAN JUN

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63.16

73.16

83.16

93.16

103.16

113.16

111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111 111

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Categ 18 Source _nopic

J our Mois

Données21

12

10

Demande constante de 96 véhicules par jour couverte par deux batchs: une arrivée de 43 véhicules un départ de 12 véhiculesune partie fixe de 63 véhicules

Sometimes OR is painless ! Solves to optimality with a MIP Easy to compare to previous

solution Easy to sell Easy to extend => more batches,

wider time window, plug with long term purchase application

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3rd Story : DIGITAL PRODUCTION A job shop problem with machines,

stockers, people and trolleys Semiconductors : Billions € spent in

the plant, almost no tool for optimization before “FAB300”

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PR

I_R

S2

03

ST1

07

ST1

08

ST1

14

ST?

LE2 LE1

LE3

TM

7 0

1

TM

7 1

5

TM

7 1

4

TM

7 1

1

TM

7 1

2

TM

7 1

3

TM

7 1

0

TM

7 0

9

TM

7 0

8

TM

7 0

7

TM

7 0

6

TM

7 0

5

TM

7 0

4

TM

7 0

3

TM

7 0

2

OV

1O

V2

OV

3O

V4

CD

8C

D7

CD

6C

D5

CD

4C

D3

CD

2C

D1

Scenario :déroulement processus (1 lot, 1 niveau)

NP is not good for CRM

CP dedicated ILOG SCHEDULER LNS Problem tackles only small instances

Improve LNS Use customer heuristic Forward : “warm rescheduling” with

“encours”

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TRIPS/TIMES O-D

05:00

06:00

07:00

08:00

09:00

10:00

11:00

12:00

13:00

14:00

15:00

16:00

17:00

18:00

19:00

20:00

21:00

22:00

23:00

TRIP OD224 LON-YOR                                      

TRIP OD225 LON-YOR                                      

TRIP OD226 LON-LEE                                      

TRIP OD227 LON-YOR                                      

TRIP OD228 LON-YOR                                      

TRIP OD229 LON-LEE                                      

TRIP OD230 YOR-LEE                                      

TRIP OD231 LON-YOR                                      

TRIP OD232 LON-LEE                                      

TRIP OD233 LON-YOR                                      

TRIP OD234 LON-YOR                                      

TRIP OD235 LIV-LEE                                      

TRIP OD236 LON-YOR                                      

TRIP OD237 LON-YOR                                      

TRIP OD238 LON-LEE                                      

TRIPS MAY REQUIRE A SPECIFIC SET OF SKILLS

4th story : Generating Cab Moves Covering with Shifts

VRO-1 : Duties       

Base 1

Base 2

Base 1

Base 2

LON-YOR0D224

LEE-YOR0D242

YOR-BIR0D289

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OPL CP syntax to get rid of cycles

nbLegs[Source] == 0;

forall(c in CaBMovesSource : c!=Source)

{

(prev[c]!=c) => (nbLegs[c] == 1 + nbLegs[prev[c]]);

(prev[c] == c) => (nbLegs[c] == 0);

}

Use OPL5.2 : one week compare to 3 years !

Solver Component

Constraint Programming (CP)

(Ilog Solver)

Specific constraints

Simplex (LP)

(Ilog Cplex)

MIP

(Ilog Cplex)

Column

Generation

« Shortest path »

Algorithm

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OAAS other stories…

Work together : one consulting company XXXX Military Communication QOS expected : assign radio gears under

constraints Perfect MIP model (100,000 binary variables,

good solution after 30 sec) Nobody to code : J2EE expected with DB XXXX ROSTUDEL TELASIDE SPRING + HIBERNATE (MySQL...) + CPLEX JAVA

MOVING FORWARD

“People on the Operations” enjoy mature code and products

A new market for consulting and support , besides traditional OR consumers

The fish is ready to byte : the door is open for “Serious OR” with “Huge” volume of data.

TV Add Campaign MIP : 100,000 rows 155,000 variables (100,000 booleans) 2 millions Non Zeros

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Questions ?