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IBM Research – Business Analytics and Mathematical Sciences

Optimization-Based Solutions: Smarter Decisions for a Smarter Planet

Dr. Irv Lustig

Manager, Optimization and Mathematical Software

Business Analytics and Mathematical Sciences

IBM Research

© 2013 International Business Machines Corporation 2


The Analytics Landscape

Based on: Competing on Analytics, Davenport and Harris, 2007 Degree of Complexity

Com

petitive A

dvanta

ge

Standard Reporting

Ad hoc reporting

Query/drill down

Alerts

Simulation

Forecasting

Predictive modeling

Optimization

What exactly is the problem?

What will happen next if ?

What if these trends continue?

What could happen…. ?

What actions are needed?

How many, how often, where?

What happened?

Stochastic Optimization

Descriptive

Prescriptive

Predictive

How can we achieve the best outcome?

How can we achieve the best outcome

including the effects of variability?

Advanced A

naly

tics

http://www.spss.com/



The Science of Better Decisions

What to build,

where and when?

How to best allocate

aircrafts and crews?

Risk vs. potential reward

Inventory cost vs.

customer satisfaction

Cost vs.carbon

emission

Optimization helps businesses:

• create the best possible plans

• explore alternatives and understand trade-off

• respond to changes in business operations



What Can Optimization Do?

• Optimization helps businesses make complex decisions and trade-

offs about limited resources

– Discover previously unknown options or approaches

• Automatically evaluate millions of choices

– Automate and streamline decisions

• Compliance with business policies and regulations

• Free up planners and operations managers so that they can leverage their expertise

across a wider set of challenges

– Explore more scenarios and alternatives

• Understand trade-offs and sensitivities to various changes

• Gain insights into input data

• View results in new ways



5

Optimization is used to solve Resource Allocation Problems

Resources

Examples of

choices to make

Capital Allocate

People

Acquire, schedule,

assign, train

Equipment Acquire, schedule, locate

Facilities Locate, schedule

Vehicles Acquire, route, schedule

Raw Material Acquire, assign

• Planning and scheduling activities

– Which are subject to complex operating constraints (e.g. limited resources, large volume of data, complex manufacturing or design processes)

– With multiple business objectives to reduce time, cost, or increase KPI’s such as productivity

• While enabling – Adjustment of changes in operating

environment – What-if analysis

Keywords: Buy, sell, schedule,

assign, staff, plan, create,

locate



When is Optimization Used?



How Does Optimization Work?



‘What’ and ‘How’ of Optimization

• Optimization helps businesses make better decisions faster through TLC+D

• Achieve Targets – All decisions are not equal. Measurable targets allow you to rank alternative decisions.

• Enforce Limits

– Not all decisions are acceptable. Some limits must be enforced.

• Make Choices

– Decisions must be made; however there are many ways to make them.

• Based on Data

– Required to measure targets, establish limits and understand relationships



Optimization

Applications



Industry Applications



11

Well-Documented Optimization ROI Cases

*Franz Edelman Competition Finalists, Science of Better, http://www.scienceofbetter.org , Published Case Studies

2 Chilean Forestry firms* Timber Harvesting $20M/yr + 30% fewer trucks

UPS* Air Network Design $40M/yr + 10% fewer planes

South African Defense* Force/Equip Planning $1.1B/yr

Motorola* Procurement Mgmt $100M-150M/yr

Samsung Electronics* Semiconductor Mfg 50% reduction in cycle times

SNCF (French RR)* Scheduling & Pricing $16M/yr rev + 2% lower op ex

Continental Airlines* Crew Re-scheduling $40M/yr

AT&T* Network Recovery 35% reduction spare capacity

Grant Mayo van Otterloo* Portfolio Optimization $4M/yr

Pepsi Bottling Group Production Sourcing $6M inv reduction + 2% fewer miles

NA Brewing Company Mfg Sourcing + Distribution $150M/yr transportation savings

US Water Products Mfg Inventory Optimization $6.2M working capital reduction

http://www.scienceofbetter.org/



Applications in

Finance



Insurance Underwriting at a US Health Benefits Company

• Situation – One of the nation’s largest publicly traded health benefits companies

– Needed to upgrade underwriting system with product selection and

recommendation capabilities

• Determine optimal price, plan and options that best correspond to customer’s

requirements

• Benefits – Improve customer service & experience by automatically customizing plans from

1000s of possibilities within seconds

• Meeting customer requirements and regulatory constraints

– Improve the productivity of underwriters by eliminating ‘guess work’



Portfolio Management at Major Investment Firm

• Situation – One of the world’s largest asset managers

– Needed to better manage risk and maintain low transaction costs through their

portfolio management applications

• Fund Rebalancing: Create optimal holdings of fund assets allowing fund managers to

perform accurate index tracking, while minimizing transaction costs.

• Trade Crossing: Match thousands of assets in buy orders against similar assets in sell

orders to avoid market trades and related transaction costs

• In-kinding: Avoid transaction costs by directly transferring portfolio values into their

targeted funds

• Benefits – Achieved competitive differentiation with the ability to reconcile risk/return

objectives, fund policies, and regulatory guidelines

– Saved $500 million in transaction costs for their clients



What if you could raise an entire country’s economy through more efficient securities transactions?

• IBM ILOG CPLEX Optimization Studio

• IBM System p5 running AIX

“By building a unique technology solution for our securities services, we now

better serve the Mexican Financial Community and trading partners. We are

very proud that this solution has played a key role in helping elevate the

economy of Mexico.”

Jaime Villaseñor

Chief Risk Officer, INDEVAL

Indeval was looking for a solution to process security transactions in real time, rather than on a daily basis, to provide the best service to the Mexican Stock Exchange and be more cost effective for trading partners.

The need

Indeval (Mexican Central Securities Depository)

What Makes It Smarter

By integrating a more robust platform, Indeval is completely transforming the way it serves the stock exchange trading brokers and the way the Mexican Financial Community used to operate, taking the trading activity in the country to a new level. Trading operations are now being reconciled and completed faster and more efficiently, increasing the number of operations the organization can perform each day and lowering the liquidity requirements of traders. With immediate data on market fluctuations and movements, investors are armed with the right intelligence to make informed decisions and react the moment changes occur instead of a day later. Thanks to the new system, Mexican economic performance has improved, reducing its “Country Risk” factor qualification among worldwide financial analysts.

Business Results

– Real time reconciliation and completion of trading operations for more than

USD$250 B in average, every day

– Reduced liquidity requirements for trading partners by 52 percent

– Increased the volume of operations by 26 percent

– Reduced the costs of each trading transaction for electronic trading facilities,

the Stock Exchange and trading brokers

– Enhanced Mexico’s risk status among analysts

Solution Components

A private securities depository organization in Mexico implements a customized solution to reconcile and complete trading

operations faster and more efficiently.



Applications in

Energy and Utilities



Success Story – Unit Commitment at REE

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

Business Problem – Use exact mathematical methods to replace the

approximate, heuristic methods Red Eléctrica de España, in charge of

managing the Spanish national power grid, had been using for the last 20 years



Benefits for REE

• The implementation of OPL/CPLEX and ODM 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 CO2

annually.



Success Story – Pumped Storage Optimization at a Mid-

Western Utility

• 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

Business Problem – Maximize market impact of the utility’s pumped

storage plant by optimizing its operating schedule to Independent

System Operator’s (ISO) market signals



Benefits for Pumped Storage Optimization

• 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



Success Story – Market Clearing by Energy Market Company

• 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

Business Problem – Ensure a reliable source of electricity at the lowest

cost for the National Electricity Market of Singapore, first wholesale

electricity market liberalized in Asia



Benefits for EMC

• 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 in developing and maintaining the

MCE



Success Story – E.ON Ruhrgas optimizes purchasing and storage of

natural gas

• Using IBM® ILOG CPLEX, E.ON Ruhrgas developed an optimization solution that identifies the margins for the quantities of purchase contracts and performs sensitivity analysis to identify risks.

• CPLEX solves very large, real-world optimization problems, while providing the speed required for interactive applications.

• The system addresses problems ranging in size from 11,000-140,000 decision variables, 500-80,000 constraints and 50,000-1,300,000 data elements.

• E.ON Ruhrgas applies the results in managing purchase contracts and storage facilities, determining pipeline capacities and negotiating purchase costs.

Business Problem – Strengthen its entire natural gas supply chain from

the wellhead to the burner, as it expands beyond its home market to the

rest of Europe. Minimizing costs by optimizing activities for purchase

contracts and storage facilities became key to the company’s business

operations.



Benefits

• Using CPLEX, E.ON Ruhrgas’ pricing and storage optimization system offer:

• Better planning and decision making.

• Greater competitiveness, as it allows E.ON Ruhrgas to react quickly to market

changes.

• Ability to analyze a large number of scenarios in trying to find the best solution for

optimizing activities.

• CPLEX provides the fastest, most reliable implementation of the fundamental

algorithms for solving mathematical optimization problems. This gives E.ON Ruhrgas

a true competitive advantage, as the company can respond rapidly to changes in the

gas market.



Applications in

Transportation



Sample Applications in Airlines (1)

• Crew Scheduling – Determine rotations of crews

• Maximize utilization

• Route crews through network

• Obey time constraints

• Fleet Assignment – Determine assignments of types of planes to flight – Minimize total fleet cost – Meet passenger demand – Obey connection time constraints – Schedule maintenance

• Ground Staff Scheduling – Determine schedules of shifts

• Obey labor requirements

• Minimize number of needed personnel – Determine rosters

• Assign people with right skills to right jobs

• Handle variability of staff availability



Sample Applications in Airlines (2)

• Gate Allocation – Allocate flights to gates

– Maximize utilization

– Obey schedules

• Revenue Optimization/Yield Management – Determine number of seats to offer at each price

– Maximize Revenue

– Allocate different seats on same flight to different connections

• Irregular Operations due to schedule interruptions (e.g., weather,

9/11) – Crew Rescheduling

– Fleet Reassignment



Transportation Planning at a Large Tire Manufacturer

• Situation – $150+M/year transportation budget

– Needed to manage hubs, driver assignments, & for-hire vs. private fleet

decisions

• 300 dealers, 15000 orders/month, 1000 trucks

• Results analyzed by 100 planners every morning, feeding 1500 users

• Benefits – Saved several % off transportation budget

– Improved supply/demand match while increasing service levels

– Better planning granularity (¼ hour)

– Better able to foresee bottlenecks and transports

– Staff able to manage more orders



Rolling Stock Allocation at Netherlands Railways

• Situation – Precisely matching trains and their cars to expected user traffic is crucial for a railway to keep costs down

and service on time. – Netherlands Railways transports more than 1 million passengers a day in its own country, works with

partners in Germany, Belgium and France, and a subsidiary in Great Britain that carries more than 300,000 passengers daily.

– Netherlands Railways’ more than 5,000 trains get passengers where they want to go in the Netherlands through a network of 390 stations and 2,800 kilometers of track.

• Solution – TIM, or Tool Inzet Materieel (Tool for Allocation of Rolling Stock) fully models the company’s operations,

including rail networks, stations and trains, and address constraints that included passenger preferences, seasonal variations in traffic and transportation regulations.

– IBM ILOG OPL Development Studio proved the right tool for modeling the railway’s operations, and IBM ILOG CPLEX the matching mathematical programming (MP) engine for deriving optimal solutions from the models.

• Benefits – The improvement in operating efficiency has been between 5 and 10 percent, netting the railway cost

savings of over €40 million annually. – Greater availability of rolling stock, as it is more accurately assigned – End users are able to make explicit choices between costs and customer satisfaction – Faster planning means shorter lead time for scheduling and rescheduling – Computer-generated plans contain fewer mistakes than manually built ones – Planners can focus on exceptional events, and eventually fewer planners may be needed to operate the

railway



Transportation Modeling at The United States Postal

Service

• Situation – USPS ships over 200 billion pieces of mail per year through a system of

transportation networks – The USPS network must consider different classes of mail including Priority,

First Class, and Standard, as well as different types of mail such as letters, flats and parcels, all of which are of different weights

• Solution – Highway Corridor Analytic Program (HCAP) uses advanced technology to

analyze USPS highway transportation scenarios – HCAP helps to identify opportunities to consolidate trucks without sacrificing

service levels, taking into account specific parameters such as routes, delivery time, truck capacity restrictions and mail class

• Benefits – $5 million in annual savings – E.J. Matto – GBS Associate Partner: “ Using optimization technology for the

transportation model helps the USPS uncover opportunities to streamline areas of long-haul transportation through consolidation.”



Applications in

Consumer

Packaged Goods



Supply Chain Network Design for a Food Manufacturer

• Business: A leading CPG product manufacturer with a wide range of food products – Multiple production facilities across globe – Multi-tiered manufacturing process – Demand is forecasted to significantly increase over the next 10 years

• Questions to answer: Where to expand in a tightly capacitated network – Is there a benefit in expanding within existing plants? If so, what should be installed, where and when? – Do we need new plants? If so, where and when? – Should we increase outsourcing? If so, for which products and where? – What is the best way to utilize existing plants? – What is the best long-term plan for the manufacturing network? – Is there an opportunity to source products across multiple regions?

• Project Objective: To develop robust manufacturing and distribution networks which

will deliver desired customer service at lowest cost – Models focussed on identifying and exploiting long-term structural cost advantages of

• Labor and Real Estate

• Freight & Duties

• Depreciation & Taxes



Results of Analysis for CPG manufacturer

• Regional Sourcing – Open new plants in SE Asia and Russia to serve regional markets, as well as expansion at specific plants – Identified specific cross-regional sourcing opportunities (Asia-Pacific to Europe)

• Co-manufacturing – The analysis found that it made sense to use co-manufacturing in the short term until new plants could be open – Once new plants are built co-manufacturing sourcing should be reduced to negligible amounts due to lower cost of in-house

production

• Plant Closure Evaluation – Recommended closure of specific plants; Labor cost savings outweighed freight & duty cost savings for selected plants.

• Capital Planning – Developed a detailed capital plan outlining equipment requirements by year over 10 horizon to support demand growth.



Production Sourcing at Pepsi Bottling Group

• Case Study published in Consumer Goods Technology Magazine

• Challenge: New demand patterns suddenly left PGB bottle lines operating at capacity and the peak demand outstripping instantaneous production capacity

• Goal: Create a process which continually improves the production sourcing strategy by minimizing system-wide costs, providing better customer service and creating a competitive advantage

• Results: Their goal was achieved with specific results including: – An increase in number of cases available to sell due to reduced out of stocks – Reduction in raw material and supplies inventory from $201 to $195 million – A 2% decline in the growth of transport miles even as PBG revenue grew – Increased in the return on invested capital

• “ILOG supply chain applications provided us the means to implement a 21st century supply chain by optimizing inventory, reducing costs and increasing sales” -- Paul Hamilton, VP Global Supply Chain, Logistics and Strategy



Inventory Target setting at Apparel Manufacturer

• Situation: – Low inventory turns throughout the network

– Required a formalized process and system for setting ‘Target Inventory Levels’

across all the divisions and brands of manufacturer for all SKUs

• Solution: – Create – Target Inventory Levels with IBM ILOG Inventory Analyst

– Users manage the exceptions with the ability to override/approve values within

Inventory Analyst

– Inventory Analyst is the central repository for Inventory Targets.

– Targets are fed to multiple ERP planning systems including SAP, Manugistics

and i2.

• Benefits: – Reduction in Inventory Levels

– Improved customer service

– Standardized, formalized process for setting Target Inventory Levels

– Solution can be rolled out with minimal training for users.



Applications in

Manufacturing



Mine Planning at a Large Diversified Mining Company

• Situation – Large diversified mining company with 700 digs sites (or pods) producing

metals, petroleum and other natural resources

– Needed to determine where and when to dig to obtain a desired mixture of

mineral content and ore grades

• While matching projected annual demand

• Considering a multitude of factors including: inventories, set-up costs, royalty

obligations, equipment availability, etc.

• Benefits – Cost savings of 5%, or more than $35 million

– Plans created in days, instead of months

– Long-term planning capabilities with ability to explore infinite what-if production

scenarios



Production Scheduling at Nissan

• Situation – Sunderland, UK was already Europe’s most efficient car production facility at the

time

– Asked to support a 3rd car model

• Wanted to accomplish this without building 3rd production line

• Benefits – Able to produce the 3rd model on the existing two lines with improved Detailed

Scheduling system built by IBM ILOG PS

– Increased capacity (potential production) by 30%

– Schedule adherence increased to 90%



Supply Chain Network Design in Petrochemicals

• Business: A European based petrochemical company is trying to optimize the distribution network

and consolidate DCs. – Currently owns 5 production facilities and 14 DCs.

• Project Objective: Understand the optimal number and locations of DCs

Closed DCs

Baseline Distribution: 14 DCs Total Cost: €22.0 M

Avg. Service: 308 km Detailed Service: 29% within 200km

Cost Optimal Distribution: 8 DCs Total Cost: €20.4 M

Avg. Service: 360 km Detailed Service: 21% within 200km

Optimization Drivers • Demand to/from matrix • Capacity by facility • Cost by facility • Transportation costs • Service constraints • Min flows for new lanes • Carbon emissions



Concluding

Remarks



Optimization is Everywhere

• Applications in Multiple Industries

• Calculable ROIs, with paybacks within months, sometimes even weeks – Capital expense avoidance or deferral

– Operating expense reductions

– Total revenue, revenue mix, and margin improvements

• Improved customer satisfaction – Provide better and more customized customer service

• Improved employee satisfaction – Satisfy schedule preferences while improving productivity

– Better planning and scheduling processes

• Better Decisions

• Faster Decisions

• Smarter Decisions for a Smarter Planet



Merci

Grazie

Gracias

Obrigado

Danke

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