Long Range Decision Support System Design Overview Institutional Knowledge Issues unresolved

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Long Range Decision Support System- Design
Overview - Institutional Knowledge-Issues
unresolved

• Transport Modeling Software Development
• 8th April 2005
• Bharat Salhotra
• Bharat.salhotra_at_gmail.com

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Transportation IR

• Key Facets
• Network Industry
• System wide view is critical
• Diversity of Traffic / Operations
• Capacity Implications
• Dynamic
• Need for databases to be updated
• Large of Interrelated variables

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ANSWERING QUESTIONS IN SEQUENTIAL ORDER IS NOT
POSSIBLE DUE TO INTERDEPENDENCIES
Interdependent variables of network planning

• Market Demand

• Traffic /Train Mix

• Train speed differential

• Types of Locos/Wagons

Solution Develop a DSS with three objectives

• Capacity increase of marshalling yards

• of stops for passenger trains

• Capacity of network

Model interdependencies at micro
levels Generalize interdependencies at Macro
Level Assess bundle of Investments based on
environment
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• Deterioration of infrastructure

• Network quality

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• Introduction of high-speed trains

• of yards/ traction change points

• Quality Standards for freight traffic/ passenger
  traffic

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• Throughput

• Complexity in Route structure of freight trains

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• System Optimization
• vs.
• Subsystem Optimization

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Need for LRDSS

• Provides important desktop information for
  planners / decision-makers for
• Investment planning/project screening
• Market analysis
• Financial impact analysis
• Funds Requirement

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LRDSS Salient Features

• Integrative Character
• Interdisciplinary
• System wide Analysis
• Simultaneous /Sequential Analysis
• Improvements in Technology/ Operating Policy
• Commodity Flows
• Routing Plans

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LRDSS Salient Features

• Customized GIS Interface
• Integration of different data by location
• Evaluate alternative routes
• Exhibit pattern of traffic flows
• Strong Decision Support
• Prioritize Investments
• Position Services to optimize market share.
• Analyze Funds required by key year

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LRDSS Salient Features

• Strong Decision Support
• Strategic Level Tool
• What-if Analysis (With/Without)
• Sensitivity Analysis
• Information based Data Driven.
• Iterative Evaluation
• Modular Design

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LRDSS for Decision Support
Five Year Plans
Strategic Level
Annual Plans
PLANNING PROCESS
Models to support different time horizons
Integrated LRDSS
BCAM DAF, FPM
FPM
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Broad Structure of Model
Market Analysis
Supply Analysis
GIS
Traffic Forecasting
Facility Performance
Demand Analysis
Traffic Assignment
Financial Forecasting
Cost Benefit Analysis
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Facility Performance
SUPPLY SIDE
NETWORK

TERMINALS
LINKS
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Rail Performance Model Determine ability to carry
traffic
LINK TYPE
SPEED COST CALCULATOR
TRAIN TYPE
Cost Curve
OPERATING RULE
TRAFFIC
Speed Curve
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RAILS Overview

• Two Modules
• Train Performance Calculator (TPC)
• Train Dispatch Simulator (TDS)
• TPC
• Single Train running on a section
• Level of interference 0
• Running determined by track profile and train

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Train Performance Calculator

• Uses empirical formulae
• Follows TE/Speed Curve, braking curves of
  locomotives
• Rolling resistance of coaches
• Train resistance, grade resistance, air
  resistance based on Davis Co-efficient
• Train treated as a series of points

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Train Performance Calculator
TRACK PROFILE
LOCOMOTIVE
TRAIN PERFORMANCE CALCULATOR
TRAIN PROFILE
COACH
WAGON
RUN TIMES Fuel Consumption Speed Profile
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TPC Output (Track Profile)
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Train Performance
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TRAIN DESPATCH SIMULATOR
Set of Trains
Track File
Run Times File
Station File
Train Types File
Parameter File
Schedule File
Scenario
Special Events File
Simulation results
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Train Dispatch Simulator

• Simulates actual train operations
• Dispatches trains to resolve conflicts
• Allocates resources dynamically
• Non priority based, route seeking dispatch
• Non Optimizing algorithm

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Train Dispatch Simulator

• Event based
• Useful for analyzing alternative line
  configurations
• location of LOOPS, CROSSINGS
• Establishment of Train schedules
• departure/arrival/halts of trains
• Examination of Capacity Issues
• Identification of Conflicts
• Meets and Overtakes

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Simulation

• Calibration
• Within 5 of actual situation on field.
• Congestion Capacity Modeling
• Traffic increased incrementally to obtain
• Congestion Graphs
• Estimated Line Capacity
• Scenario Analysis
• Impact of failures
• Horsepower to Trailing Load ratios
• Passenger Train Halts

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Output from FPM

• Simulation results of 17 links
• transit times congestion curves by train type
  Link Type
• impact of failures (track, signaling, wagons)
• capacity based on simulation (not charting)
• Cost Data
• working expenses by train type

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CONVERSION INTO COST FUNCTION
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Congestion Graphs
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Market Analysis and Traffic Forecast
DEMAND SIDE MODELING
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Mode Share Key Determinants(from SURVEY)

• Volumes
• High volumes (gt1 lakh TPA) high rail share if
  few destinations
• Channel Structure
• Flat distribution channels, bulk buyers favor
  rail movement.
• Flow rate
• Raw materials Production line
• Finished goods Consumption Center.
• Lead length
• Long lead traffic favors Rail
• Business Service Requirements
• JIT ,Reduced Order Quantity, Reliability
• Single to multiple suppliers

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Key Factors to Success

• Core Factors
• Reliability, Availability, Price and Transit Time
• Desirable Factors
• Connectivity, Product Suitability, Loss/Damage,
  Customer Information
• Adaptability, Customer Friendliness,
  Negotiability, Access to Decision Makers
• Ease of Payment Claim Processing Time

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Market Share Analysis
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Traffic Forecasting Module

• Objectives
• Determine Production Consumption Functions by
  Commodity for TAZs
• Forecast Origin Destination Flows by
• Commodity
• Key Years (2006-07 2011-12)
• Identify high growth areas
• loading
• unloading terminals
• Origin Destination Routes

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Traffic Analysis Zones
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Methodology

• Different models used for different commodities
• GAMS Linear Programming Model
• Assigns traffic by minimizing transportation
  cost.
• Furness Trip Generation Model
• Generates OD flows based on movement pattern in
  the base year
• Factoring
• OD flows are projected based on growth rates.

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Traffic Assignment Module
DEMAND SUPPLY MODELING
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Traffic Assignment Module

• Operation Research based Freight Network
  Equilibrium Model.
• Objective function Minimize total cost of
  carrying traffic
• Assign OD flows on paths using least impedance.
• ( S congestion cost on links/nodes )
• Each path consists of series of links and nodes.
• Path Cost aggregated cost of traffic movement
  over each link and node.

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Traffic Assignment Module

• Basic Inputs to the Model
• I Demand Side
• Existing and Future Traffic
• Commodity wise flows between pairs of points
• Traffic for 200102, 2006-07, 2011-12
• II Supply Side
• Existing and Future Network
• Sections as well as their Cost Characteristics
• Stations as well as their Cost Characteristics

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Network Databases

• Two distinct database representing IR network
• Railline Database
• Railnode database
• 1796 links 1531 nodes for base case
• Nodes Database contains information like TAZ,
  Transshipment point, Rail terminal/yard, Traction
  change point, reversal etc.

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Attributes of a Section
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Methodology for Assignment

• Base Year Assignment on Preferred Paths
• Future Years
• Assignment on both Preferred Shortest Paths
• Assignment with committed works
• Sequential/Simultaneous

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Analysis of TAM Results

• Outputs
• Commodity wise traffic on each link.
• ODs that use a particular link.
• Lowest Cost Route path between pairs of points.
• Utilization of each Traction Point.
• These reports can be compared for alternative
  scenarios.

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Variables Handled

• Data Size Spread
• 900 900 10 OD matrix elements
• 15,000 Rail Paths
• Each Path has average of 50 links
• Each link has commodity wise congestion function
• 3 sets of data, by key year

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TAM-Conceptual design

• Replicate Shippers Behavior
• What commodity from where to where?
• Replicate Carriers Behavior
• What commodity, what route, what train type
• Non Linear Programming Optimization Solver
• MINOS

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Sub Modules of TAM

• Network Processor
• create a logical multi modal network
• access /egress links,
• transshipment links, traction change points,
  nodes
• Output consists of Forward star data structure to
  be used as input to k path algorithm
• Path generator (K-Short)
• creates shortest paths between two O-D Pairs
• Input to Solver

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Sub Modules of TAM

• Carrier Input Processor
• Generates MINOS input file
• Represents full specifications of carrier model
  with unit costs specified as a real valued
  function of path flows (non linear)
• Post processor
• Interprets MINOS solution file.
• Interfaces with GIS
• Query based GIS interface allows graphical
  display of bottleneck links, flows etc.

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GIS LRDSS

• Avenue based Path Editor used to check paths
  generated by kshort algorithm
• transshipments, traction change, reversals
• create new paths via certain given stations
• User Interface to facilitate Data Analysis
  through
• Data browser
• Query Builder
• Chart generator

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Path Editor to display/define routes
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Path Editor
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Cost Benefit Analysis Investment Planning
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Utility of LRDSS

• LRDSS is a powerful tool for enabling a
  pre-feasibility analysis.
• Results are only indicative
• micro modeling to gauge impact of specific
  investment/policy initiatives.
• availability of financial resources needs to be
  matched with priority of projects.

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Phase III

• Strengthen existing model with
• Terminal Analysis
• Multi-Modal Traffic Analysis
• Benchmarking Operations
• Improve Information availability on desktop of
  decision-makers
• Interconnect

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Terminal Analysis Module

• Objective
• Develop a better understanding of terminal
  operations
• Use Process modeling to estimate detentions and
  impact of such detentions
• Evaluate investment options to minimize
  detentions and improve efficiency at terminals
• Simulation Model instead of a Numerical Model

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Stylized Diagrams

• Terminal representation using six standard
  features
• Entry Exit Points
• Support Yards
• Customer Sidings
• Platforms
• Intersections
• Connections

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Facilities Database

• Associated with a Facility are 3 types of fields
• Time related fields
• Capacity related fields
• Resource related fields
• E.g. a support yard would have fields specifying
• Examination Time (Average, Minimum, Maximum)
• Shunting Engine Attach/Detach Time TIME
• Waiting for Train Engine Time TIME
• Number of Tracks CAPACITY
• Number of examination gangs RESOURCE

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Trains Database

• Brain Train
• Trains have an ID, type and commodity associated
• Arrival Day and Time
• Predefined Route assigned to the train
• Route Descriptions
• START at ENTRY POINT
• Sequence of FACILITIES a train has to USE
• Quantum of RESOURCE TIME required
• END at EXIT point

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TKD
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Simulation

• Terminal Process model simulates
• Movement of trains on routes through Terminal
• Delays of trains due to limited resources
• Delays due to crew change
• Loading/unloading at customer siding
• Interaction with passenger trains sharing
  facilities with goods trains
• Disruptions at facilities
• User Interface

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Model Outputs

• Train delays (process times and non-process
  times) by train
• Assignment of delay to
• facility
• resource
• Activity summary of utilization of all of the
  facilities and resources, including
• time spent in examination, loading/unloading
• track usage
• Feed investment analysis

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Multimodal Corridor Analysis Model
Target Year Total Flows
Traffic Growth Rate by Commodity OD
Freight Flows in Corridor
Qualitative Preference data
Mode Split Model
Target Year Rail Container Flows
Cost Benefit Analysis
Operational Statistics
Infrastructure Requirements
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Mode Split Model

• Parameters
• Price
• Transit Time
• Service Quality Index (Reliability, Availability,
  Frequency, Loss Damage)
• Product Suitability
• Form
• Cobb Douglas

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Multimodal Corridor Analysis Model

• Estimate Total Traffic
• Estimate Operational Requirements (Throughput,
  Trains, Lifts etc.)
• Estimate Capital Requirements (Infrastructure,
  Rolling Stock, Equipment)
• Estimate Cash Flows
• Calculate IRR

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Resource Requirements

• Terminal Resources
• Land
• Rail Lines
• Equipment (stackers, trailers, gantry cranes)
• Gates
• CW
• Rolling Stock

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Scenario Analysis

• Assess different Investment alternatives
• Do minimum (only soft changes)
• De-Bottlenecking
• Full Fledged Corridor
• Assess Pricing Strategies
• Assess Impact of Service Levels

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Interconnect-LRDSS Other IR Databases
Planning Data (Project Data)
MIS (annual summaries e.g. Traffic)
Engineering Data (Improvements and Unit Costs)
Railway Board/ LRDSS Databases (Scenario Data)
FOIS (annual summaries e.g. op. stats)
Financial Data (e.g. budgets)
Zonal Railway Data (Line and Section Data)
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KEY AREAS FOR COLLABORATION

• LINE CAPACITY SIMULATOR
• TRAFFIC ASSIGNMENT MODEL
• PATH GENERATOR
• OPTIMIZATION ALGORITHM
• PASSENGER TERMINAL DESIGN

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THANK YOU