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Lecture 32: Scheduling Systems 2
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Outline Scheduling Systems are
Information Systems But even harder to build
Are We Solving the Right Problem? What does a human scheduler do? Are we solving the “real” problem? Garbage in, garbage out
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Readings
P Ch 13.7
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Scheduling Systems are Information Systems
Everything you learned in MIE350 applies here Why do you build a system? How do you build a system? How does the system get used in an
organization? Use cases Data modeling, process modeling, …
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But It’s Worse
At the core is (usually) a mathematically hard problem
Risk & uncertainty If such a high percentage of normal IT
projects fail, what about projects where the core mathematical problem is intractable?
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And Even Worse
Scheduling experts tend to be interested in the math and algorithms They may not talk to the “real users” or
may be even the system builders! People who understand OR are not the
people who understand information systems
one reason why InfoEng is important to OR people and why MIE350 is a core course
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And Worse Again
“… a certain proportion of the theoretical research done over the last couple of decades is of very limited use in real world applications”
– Pinedo p. 339
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And Worse Again
“40 years of research in nurse scheduling and “very few of the developed approaches are suitable for directly solving real world problems”
– Burke et al. p. 469
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Are We Solving the Right Problem?
Scheduling is important in the real world economically, environmentally, …
To advance scheduling should we concentrate on the OR or the Information Engineering?
What is the right problem?
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What Tool Does the Most to Increase Schedule Quality?
Suppliers
Customers
Factoryfloor
The rest of theinformation
system
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What Does a Human Scheduler Do?
Negotiates Can I deliver half now
and half later? Can I substitute product
X for product Y? Can you push this job
through the factory faster?
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What Does a Human Scheduler Do?
Prioritizes Job X is more important
because the customer is very big
Job Y is more important because we delivered their order late last time
Job Z is more important because we are phasing out that product
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What Does a Human Scheduler Do?
Spends money to relax constraints Can we run a 3rd shift? Can we rent capacity
from a competitor? Can we go below safety
stock to meet this order?
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What Does a Human Scheduler Do?
Changes the problem! We have no mid-size
cars, would you like an SUV?
We have no tables available at 8 PM, how about 7:30?
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The Scheduling Problem
SchedulingProblem
Customer Demand
Forecast Demand
Quality Requirements Resource Availabilities
Process Plans
Raw Material Supply
Preventative Maintenance
Union RegulationsMake or Buy?
Order Priorities
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Changing the Problem
Optimization techniques try to solve the problem human changes the problem so it can be solvable!
What the human scheduler does is based on knowledge not represented in the scheduling problem! Think of the experience and information that the human needs
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Another View of Scheduling
We should be building information systems that give humans the information required to make better decisions
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Are We Solving the Right Problem?
Scheduling is important in the real world economically, environmentally, …
To advance scheduling should we concentrate on the OR or the Information Engineering?
What is the right problem?
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Real World Scheduling [MacKay88] “Pathological” job shop
80 acts/job, 300 res, 5000 active jobs all orders are behind schedule
Uncertainty set-up time varies from 2 days to 6 weeks processing time: can vary by 100% raw material arrival high-priority orders decreased worker productivity
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Uncertainty
We don’t really know the exact processing time of an activity
We don’t know when new orders will arrive or if/when existing orders will be cancelled
We don’t know when machines will break down or how long it will take to fix them
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In practice …
The shop floor deals with the problem but what relation does the executed
schedule have to the original schedule? A schedule is only “optimal” to the
extent that the real world follows theassumptions madein the schedulingmodel
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This is All Very Depressing
We’ve just spent 13 weeks learning about techniques that solve the wrong problem with the wrong data