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ILOG Optimization
Hogyan lehet a legtöbbet elérni a
legkevesebbért?
ILOG optimalizálással egy változó világban!
Ahogy mások csinálják…
Kátai Ferenc, Ph.D.
IBM ILOG CPLEX Optimization Studio PLM
© 2009 IBM Corporation
ILOG Optimization
Why optimization?
Because – hopefully – you
get something “better”!
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© 2009 IBM Corporation
ILOG Optimization
How much better?
You have to measure it!
Then you will know!
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© 2009 IBM Corporation
ILOG Optimization
The basics…
 Every (math) optimization is about measurable
things. E.g.
– Reducing Costs (minimize)
– Increase profit (maximize)
– Using/investing in less resource (minimize)
– Making a shorter maintenance schedule (minimize) and
therefore the plant’s uptime is longer → more revenue
– making the shortest routing schedule → less cost + better
customer care
–…
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© 2009 IBM Corporation
ILOG Optimization
The science of Better Decisions
How to best allocate
aircrafts and crews?
Optimization helps businesses:
inventory cost vs.
customer satisfaction?
• create the best possible plans
• explore alternatives and understand trade-off
What to build,
where and when?
• respond to changes in business operations
Risk vs. potential
reward?
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Cost vs. carbon
emission?
© 2009 IBM Corporation
ILOG Optimization
How Optimization Works
Targets & Goals
Limits, constraints,
Rules
Data
CPO
CPLEX
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Choices & Decisions
KPIs
TOOLS
Studio/IDE
OPL
© 2009 IBM Corporation
ILOG Optimization
Extreme ROI
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© 2009 IBM Corporation
ILOG Optimization
Extreme ROI In Telco/Media/Finance/Energy
Company
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Business problem
ROI
Telco Co. - US
Network recovery
35% reduction of spare capacity
Broadcasting Network US
Sales process planning
In 1996-200 increased revenue by
200M$, reduced rework by 80%
Defense Force - Africa
Force/Equipment planning
1.1b$/year
Financial Service
Provider - US
Cash Inventory Mgmt
Reduced replenishment cost by 55%
+ reduced cross-shipping fee by
63% (daily cash dispersion is
200M$)
Investment Co. - US
Portfolio planning
For 600 clients with 185b$ valued
portfolio 100M$< saving on
transaction cost
Investment Co. - US
Portfolio optimization
4M$/year
Power Generating Co. US
Hydro-power generation
0.8M$/year reducing cost
Power Generating Co. Spain
Unit commitment
130K$(100K€)/day cost reduction
© 2009 IBM Corporation
ILOG Optimization
Extreme ROI - In Transportation/Logistics/Hotel
Company
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Business problem
ROI
Postal service - US
Air Network Design
87M$/2years + 10% fewer planes
Postal service - US
Network design
5M$</year cost saving
Logistics SW Co - US
Routing application
0.6M$/year reducing cost
Airline - US
Crew rescheduling
40M$ in a year
Railway Co. - FR
Scheduling pricing
1.1b$
Railway Co. – The
Netherlands
Time-tabling/rolling stock
optimization/crew
scheduling
27M$(20M€)/year reducing
operational cost +
54M$ (40M€)/year increase of fare
revenue
Hotel SW Co. - US
Hotel planning
Some customers reduced cost by
more than 10% (50M$)
© 2009 IBM Corporation
ILOG Optimization
Extreme ROI - In Manufacturing
Company
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Business problem
ROI
Semiconductor Co. - US
Procurement Mgmt
100-150M$/year
Semiconductor Co. Korea
Semiconductor mfg
50% reduction in cycle time
Mining Company Australia
Mine production planning
5% (35M$<) cost saving
Mining SW Co. - US
Mine operation planning
20M$< value increase (2-3%
increase of b$ minevalue)
Car maker - US
Planning of sourcing
>50M$/5years cost saving +
40M$ upfront investment savings
Car maker - UK
Car mfg
Saved the cost of building a 3rd
production line + investment
payback in three days
Steel maker - Korea
Steel mfg
Reducing 30-40% stock (on
10b$/year revenue)
Beverages maker - US
Production planning
1M$</year reducing cost
2 Chilean Forestry firms
Timber harvesting
20M$/year + 30% fewer # of trucks
© 2009 IBM Corporation
ILOG Optimization
How about the energy
market?
What are the issues?
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© 2009 IBM Corporation
ILOG Optimization
Hot Button Issues In Energy and Power
Climate
change
• Renewable
energy
• Energy
efficiency
• Low emission
generation
• Transportation
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Grid
Market
Enterprise
utilization restructuring,
IT
and
regulations
reliability
• New contract
and pricing
policies
• Performance
penalties
• Increased
maintenance
expense
• Increased T&D
investment
• Gas/electric
market
convergence
• Market design
and bid
optimization
• Resource
adequacy
• Price spikes
and gaming
• From better
information to
better decisions
• Empowering
business users
• Data collection
lags data
management
© 2009 IBM Corporation
ILOG Optimization
Optimization Problems in the Energy and Power Industries
 Generation/Resource Planning
 Unit Commitment/ Economic Dispatch
 Hydro/Thermal Scheduling
 Optimal Power Flow/ Security
Constrained Dispatch
 Network Planning
 Contract and Risk Management
 Nuclear Power Outage Scheduling
 Power Plant Maintenance
 Manpower planning
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© 2009 IBM Corporation
ILOG Optimization
DTE (Detroit Edison) - US
 Founded in 1903
 Investor-owned utility
 Serves most of Southeast Michigan
 2.2 million customers
 11,080 MW system capacity
 Fleet:
–
9 fossil-fuel generating plants
–
Enrico Fermi Nuclear Generating
Station
–
Co-owned Ludington Pumped Storage
Power Plant
© 2009 IBM Corporation
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7/18/2015
© ILOG, All rights reserved
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ILOG Optimization
Pumped Storage Optimization at DTE
Business Problem – Maximize market impact of Detroit Edison’s
Ludington Pumped Storage Plant by optimizing its operating schedule to
Midwest Independent System Operator (MISO) market signals
Constraints
– Market Price forecast
– Reservoir capacity
– Unit generation and pumping capacity
– Generation and pumping efficiency
– Reversible turbines cannot start in
pumping mode above certain reservoir
level
– Limit on pumping sessions: only once a
day
– Unit availability
– Unit startup interval & ramp rate
– Initial and final reservoir levels for the
period of analysis
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© 2009 IBM Corporation
ILOG Optimization
DTE Benefits
 The models are written in OPL and solved by CPLEX
 Standardized business procedure providing mathematically validated schedule
– Model finds opportunities which may not be obvious
 Helps an operator to value the water in the pond and make a decision to deviate
from the schedule in real-time
– When asked to deviate from the original schedule, gives analysis of opportunity lost so
operator knows cost of deviation
 Increased utilization of the plant
The bottom line:
– Expected improvement opportunity of as much as $8M annually with an initial goal to
achieve at least 10% of that opportunity
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© 2009 IBM Corporation
ILOG Optimization
Red Eléctrica de España - Spain
 it was created in 1985, it took over the transmission grid and the
operation of the Spanish power system, well before the recent
world-wide trend towards the segregation of activities, establishing
transmission as a separate activity from generation and
distribution. This marked a radical change in how the Spanish
power sector operated and served as a model for other countries
when liberalizing their power sectors.
 Red Eléctrica was the first company in the world dedicated
exclusively to power transmission and the operation of electrical
systems. A pioneer in its field, the company occupies a position of
leadership today in these activities.
 REE is required to effectively-manage transmission grid to work
properly in coordinated operation of the generation-transmission
system, to ensure that demand would be satisfied at all times.
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© 2009 IBM Corporation
ILOG Optimization
Unit Commitment at REE
Business Problem
• unit commitment application replacing their heuristics/approximation-based method
• Incorporating windfarms and weather forecast into the plan
“The methodology applied until now … was an
interactive methodology, which did not guarantee
an optimum solution. There were many difficulties
in the smaller systems and it was hard to find the
most viable solution. Thanks to the new
methodology, we have resolved this type of
problem.”
- Mr. Mustafa Pezic, REE Project Director
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© 2009 IBM Corporation
ILOG Optimization
Unit Commitment Example
 Minimize Start-up + Fuel Cost
 10 generators – 1752 MW
– 2 Coal, 4 Gas, 4 Diesel
– 12 – 425 MW capacity
– Min up/down time
– Max ramp up/down rate
– Start-up cost
– Fixed + variable running cost
 Hourly load forecast for 8 days
– Peak demand 1448 MW
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© 2009 IBM Corporation
ILOG Optimization
REE Benefits
 The models are written in OPL and solved by CPLEX. The application
is based on the ODM platform. The solution has provided great
operational advantages to company’s managers and engineers
– “The new tool allows us to simplify all maintenance tasks and any changes made to the
model, which in our particular case, are very frequent.”
– “From a user viewpoint, it has brought greater trust in the solution and a significant
reduction in planning time required by users. In parallel with this, from a development
and maintenance viewpoint, there has been a significant reduction in associated costs,
as well as in the duration of the processes.”
The bottom line:
– REE reduced production costs by between €50,000 and €100,000 per day.
– REE has reduced its carbon emissions by approximately 100,000 tons of CO 2 annually.
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© 2009 IBM Corporation
ILOG Optimization
Energy Market Company - Singapore
 Energy Market Company Pte Ltd (EMC) is the
independent market operator of Singapore's
wholesale electricity market started operating in 2003
 Singapore is Asia's first liberalized electricity market
 EMC completes the connection between those who
make electricity in Singapore and those who use it.
Like a stock exchange for electricity, all of
Singapore's electricity is bought and sold through
EMC
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© 2009 IBM Corporation
ILOG Optimization
Market Clearing by Energy Market Company
Business Problem
• Ensure a reliable source of electricity at the lowest cost for the National
Electricity Market of Singapore
 Every half-hour, power companies update their rates for
selling electricity to the exchange
 EMC must assemble these rates into a mix of prices and
generation schedules that will satisfy consumer demand
at the lowest cost possible
 Using ILOG CPLEX, the Market Clearing Engine (MCE)
solves the problem within 30 seconds, addressing more
than 15,000 constraints and bounds with each trade
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© 2009 IBM Corporation
ILOG Optimization
EMC Benefits
 Using ILOG CPLEX in the MCE has helped EMC:
– Consider all possible constraints with each trade
– Achieve the lowest generation cost for electricity
offered to the Singapore wholesale electricity market
while considering system security and reliability
requirements
– Improve the performance of the electricity market
– Reduce the maintenance time for the trading system
 EMC’s IT team is more efficient maintaining MCE
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© 2009 IBM Corporation
ILOG Optimization
Electricity provider in the Long Island region - US
 Context
– The company produces and distributes electrical power
– Crew has to be allocated for equipment repair and maintenance jobs (there
are emergency jobs – broken/failing equipment)
 Assigning maintenance jobs/resources to technicians and make
their daily schedules for 2-10weeks
– Solution quality measured by: scheduled jobs per jeopardized jobs and
unscheduled jobs
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© 2009 IBM Corporation
ILOG Optimization
Maintenance Staff and Equipment Allocation 1/2
 Problem description
– Jobs with different priorities
– Skill and equipment requirements (# of skills = 50-100)
– Resources availability, possible overtime allowance, travel time between
job locations
– Resource replacements, reservation of resources for emergency jobs
– # of technicians/districts: 50-100
– # of districts: 30-100
– # of jobs to schedule in the horizon = 100-1000 - People per job: 1 person
or a crew
– # of jobs per day = 80-150
© 2009 IBM Corporation
ILOG Optimization
Maintenance Staff and Equipment Allocation – 2/2

Benefits
– Cost reduction of several million dollars per year
– Substantial improvements in customer service
– Less dependence on contractors
•
"The ILOG scheduling engine incorporated into LILCO's
Corporate Resource Management System has set the stage for a
new era in the planning and scheduling of thousands of
resources."
© 2009 IBM Corporation
ILOG Optimization
Thank you!
© 2009 IBM Corporation