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DTSTAMP:20220814T085825Z
DESCRIPTION: \n\n_LEARN HOW THE NATIONAL FOOTBALL LEAGUE (NFL) USES MATHEMA
TICAL OPTIMIZATION TO SOLVE ONE OF THE HARDEST SCHEDULING PROBLEMS IN EXIS
TENCE._\n\nAt first glance\, the NFL’s scheduling problem seems simple: 5
people have 12 weeks to schedule 256 games over the course of a 17-week se
ason. The scenarios are potentially well into the quadrillions. Making the
problem particularly hard is the necessary inclusion of thousands of cons
traints addressing stadium availability\, travel considerations\, competit
ive equity\, and television viewership.\n\nIn this webinar\, you will lear
n how the NFL began using Gurobi’s mathematical optimization solver to tac
kle this complex scheduling problem. With mathematical optimization\, NFL
planners can generate and analyze more than 50\,000 feasible schedules des
pite adding more constraints to the process every year. Now rather than sp
ending months manually constructing one schedule\, the NFL planners can fo
cus on evaluating and comparing thousands of completed schedules to determ
ine which should be selected as the final schedule.\n\nView this session a
nd learn:\n\n * How the NFL uses mathematical optimization to solve one of
the most challenging scheduling problems in existence.\n * How the NFL swi
tched from a linear to a parallel approach to optimization.\n\n
DTSTART:20210503T194500Z
DTEND:20210503T210000Z
LAST-MODIFIED:20220814T085825Z
LOCATION:
SEQUENCE:0
STATUS:CONFIRMED
SUMMARY:Keynote Webinar: Optimization and The NFL’s Toughest Scheduling Pro
blem
TRANSP:OPAQUE
X-ALT-DESC;FMTTYPE=text/html:

\n\n**Learn how the Natio
nal Football League (NFL) uses mathematical optimization to solve one of t
he hardest scheduling problems in existence.**

\n\nAt fi
rst glance\, the NFL’s scheduling problem seems simple: 5 people have 12 w
eeks to schedule 256 games over the course of a 17-week season. The scenar
ios are potentially well into the quadrillions. Making the problem particu
larly hard is the necessary inclusion of thousands of constraints addressi
ng stadium availability\, travel considerations\, competitive equity\, and
television viewership.

\n\nIn this webinar\, you will learn how the
NFL began using Gurobi’s mathematical optimization solver to tackle this
complex scheduling problem. With mathematical optimization\, NFL planners
can generate and analyze more than 50\,000 feasible schedules despite addi
ng more constraints to the process every year. Now rather than spending mo
nths manually constructing one schedule\, the NFL planners can focus on ev
aluating and comparing thousands of completed schedules to determine which
should be selected as the final schedule.

\n\nView this session and
learn:

\n\n- How the NFL uses mathematical optimization to solve
one of the most challenging scheduling problems in existence.
\n - H
ow the NFL switched from a linear to a parallel approach to optimization.<
/li>\n

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ACTION:DISPLAY
DESCRIPTION: \n\n_LEARN HOW THE NATIONAL FOOTBALL LEAGUE (NFL) USES MATHEMA
TICAL OPTIMIZATION TO SOLVE ONE OF THE HARDEST SCHEDULING PROBLEMS IN EXIS
TENCE._\n\nAt first glance\, the NFL’s scheduling problem seems simple: 5
people have 12 weeks to schedule 256 games over the course of a 17-week se
ason. The scenarios are potentially well into the quadrillions. Making the
problem particularly hard is the necessary inclusion of thousands of cons
traints addressing stadium availability\, travel considerations\, competit
ive equity\, and television viewership.\n\nIn this webinar\, you will lear
n how the NFL began using Gurobi’s mathematical optimization solver to tac
kle this complex scheduling problem. With mathematical optimization\, NFL
planners can generate and analyze more than 50\,000 feasible schedules des
pite adding more constraints to the process every year. Now rather than sp
ending months manually constructing one schedule\, the NFL planners can fo
cus on evaluating and comparing thousands of completed schedules to determ
ine which should be selected as the final schedule.\n\nView this session a
nd learn:\n\n * How the NFL uses mathematical optimization to solve one of
the most challenging scheduling problems in existence.\n * How the NFL swi
tched from a linear to a parallel approach to optimization.\n\n
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