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