Center for Engineering Logistics and Distribution (CELDi) An NSF sponsored Industry/University...
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Transcript of Center for Engineering Logistics and Distribution (CELDi) An NSF sponsored Industry/University...
1Center for Engineering Logistics and Distribution (CELDi)
An NSF sponsored Industry/University Cooperative Research Center
Logistics of Using Underground Pipelines for Freight TransportationFreight Pipeline Company
James S. Noble, Ph.D., P.E. & Mustafa Sir, Ph. D.Gaohao Luo, Anna McLaughlin, Nichole Smith
AGENDA – October 28, 2009• Problem Statement / Approach• Current Work
• Operations Optimization• Load / Unload Analysis• Simulation
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Logistics of Using Underground Pipelinesfor Freight TransportationResearch Team: James Noble (PI), Mustafa Sir, Gaohao Luo Anna McLaughlin, Nichole Smith
Sponsor: Freight Pipeline Company
Problem in context: Many large metro areas around the world are highly congested hindering the flow of freight in and out. Underground freight pipelines or tubes can reduce congestion, reduce environmental impact of freight movement and reduce overall transportation cost. Projects are currently in the evaluation stage in New York, Sydney, Shanghai and others.
Important/Expected Results• Tube network design – I/O location, flow path• Capsule dispatching / control algorithms• Cargo tracking approaches• Design of load / unloading processes• Capacity analysis
Technical Approach• Assess related logistics issues• Develop object oriented simulation model for
analyzing dispatching / control approaches• Formulate design / operation models• Development of solution algorithms• Model sensitivity analysis• Implementation scenario analysis
What can other members use?• Network design algorithms• Loading/unloading algorithms• Cargo tracking strategies• Dispatching / control algorithms
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Problem Statement
• Logistics issues associated with freight tube system – Tube network design – I/O location, flow path– Dispatch/control of capsules according to freight shipment needs
(capacity and schedule)• Tracking of cargo in transit in the pipe and in storage room
– Design of cargo loading and unloading process at freight pipeline terminals
– Capacity analysis
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• Literature review of related problem areas (i.e. pneumatic pipeline, AGV systems, rail systems)
• Determination of modeling issues– Technology constraints– # vehicles / train length– Route / network design– Buffer size / load sizes– …
• Development of simulation model (Simio) • Development of optimization models for select design
issues• Model analysis
Project Approach
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Vehicle Technology
Vehicle Rqmts- size and #
Operation- dispatching- routing
Network Design- flow path- # & location P/D
Information- ID (RFID)
Problem Domain
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O14
1
4 2
3
O13
O24
Oijk: job k in station I to destination station j.
Station
Unidirectional network
Operation Optimization
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Minimize
Subject to:
Operation Optimization
Total squared tardiness
Sequential operations
Capacity
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2
31
O12 O23
O31
Operation Optimization: Case Example
Due date
(dij)Processing Time (pij)
Number of Capsules Required (cij)
O12 1 2 1
O23 2 2 1
O31 4 3 1
We assume that there is ONE capsule in the system.
The parameters of the example are shown below:
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Operation Optimization: Case Example
Sij (starting time of Oij) Processing Time (pij) Due date (dij) Tardiness
O12 0 2 1 1
O23 2 2 2 2
O31 4 3 4 3
All three operations can be completed using one of the following 3 schedules:1. O12 O23 O31 ,then the sum of square of total tardiness = 12 + 22 + 32 = 142. O23 O31 O12, then the sum of square of total tardiness = 02 + 12 + 62 = 373. O31 O12 O23, then the sum of square of total tardiness = 02 + 42 + 52 = 41
Lingo Results
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Load/Unload Concepts
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Load/Unload Concepts
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Load/Unload Concepts
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Demand Unload Rate (mins) Lift Rate (ft/min) Buffer Size Total Time # Moved in 24 Hours
10 (expo 6) 0.01 2 0 0.0100 100
10 (expo 6) 0.5 2 1 0.5152 100
10 (expo 6) 1.5 2 2 1.6969 100
10 (expo 6) 3 2 5 4.3551 100
10 (expo 6) 5 2 10 12.2624 100
Unload Demand: 10 containers / hour, 100 / day
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Unload Demand: 40 containers / hour, 500 /day
DemandUnload Rate
(Mins)Lift Rate (ft/min)
Buffer Size
Total Time
# Moved in 24 Hours
40 (expo 1.5) 0.002 2 0 0.0020 500
40 (expo 1.5) 0.032 2 1 0.0325 500
40 (expo 1.5) 0.2 2 2 0.2173 500
40 (expo 1.5) 0.5 2 5 0.6358 500
40 (expo 1.5) 1 2 10 2.0020 500
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Unload Demand: 80 containers / hour, 1000 / day
Demand Unload Rate (mins) Lift Rate (ft/min) Buffer Size Total Time # Moved in 24 Hours
80 (expo 0.75) 0.001 2 0 0.0010 1000
80 (expo 0.75) 0.016 2 1 0.0162 1000
80 (expo 0.75) 0.1 2 2 0.1084 1000
80 (expo 0.75) 0.35 2 5 0.5096 1000
80 (expo 0.75) 0.6 2 10 1.7194 1000
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System Simulation – Small Loop