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Center for Engineering Logistics and Distribution (CELDi) An NSF sponsored Industry/University Cooperative Research Center Logistics of Using Underground.

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Presentation on theme: "Center for Engineering Logistics and Distribution (CELDi) An NSF sponsored Industry/University Cooperative Research Center Logistics of Using Underground."— Presentation transcript:

1 Center for Engineering Logistics and Distribution (CELDi) An NSF sponsored Industry/University Cooperative Research Center Logistics of Using Underground Pipelines for Freight Transportation Freight 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 1

2 Logistics of Using Underground Pipelines for Freight Transportation Research 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 % Complete 0% 100% 2

3 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 3

4 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 4

5 5 Vehicle Technology Vehicle Rqmts - size and # Operation - dispatching - routing Network Design - flow path - # & location P/D Information - ID (RFID) Problem Domain

6 6 Operation Optimization

7 7 Minimize Subject to: Operation Optimization Total squared tardiness Sequential operations Capacity

8 8 Operation Optimization: Case Example Due date (d ij ) Processing Time (p ij ) Number of Capsules Required (c ij ) O 12 121 O 23 221 O 31 431 We assume that there is ONE capsule in the system. The parameters of the example are shown below:

9 9 Operation Optimization: Case Example S ij (starting time of O ij ) Processing Time (p ij ) Due date (d ij )Tardiness O 12 0211 O 23 2222 O 31 4343 All three operations can be completed using one of the following 3 schedules: 1.O 12  O 23  O 31,then the sum of square of total tardiness = 1 2 + 2 2 + 3 2 = 14 2.O 23  O 31  O 12, then the sum of square of total tardiness = 0 2 + 1 2 + 6 2 = 37 3.O 31  O 12  O 23, then the sum of square of total tardiness = 0 2 + 4 2 + 5 2 = 41 Lingo Results

10 Load/Unload Concepts 10

11 Load/Unload Concepts 11

12 Load/Unload Concepts 12

13 DemandUnload Rate (mins)Lift Rate (ft/min)Buffer SizeTotal Time# Moved in 24 Hours 10 (expo 6) 0.01200.0100100 10 (expo 6)0.5210.5152100 10 (expo 6)1.5221.6969100 10 (expo 6)3254.3551100 10 (expo 6)521012.2624100 Unload Demand: 10 containers / hour, 100 / day 13

14 Unload Demand: 40 containers / hour, 500 /day Demand Unload Rate (Mins) Lift Rate (ft/min) Buffer Size Total Time # Moved in 24 Hours 40 (expo 1.5)0.002200.0020500 40 (expo 1.5)0.032210.0325500 40 (expo 1.5)0.2220.2173500 40 (expo 1.5)0.5250.6358500 40 (expo 1.5)12102.0020500 14

15 Unload Demand: 80 containers / hour, 1000 / day DemandUnload Rate (mins)Lift Rate (ft/min)Buffer SizeTotal Time# Moved in 24 Hours 80 (expo 0.75)0.001200.00101000 80 (expo 0.75)0.016210.01621000 80 (expo 0.75)0.1220.10841000 80 (expo 0.75)0.35250.50961000 80 (expo 0.75)0.62101.71941000 15

16 System Simulation – Small Loop 16


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