1 long range decision support system - design overview - institutional knowledge -issues unresolved...

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Long Range Decision Long Range Decision Support SystemSupport System- - Design Overview Design Overview

- Institutional Knowledge - Institutional Knowledge-Issues unresolved-Issues unresolved

Transport Modeling & Software Development Transport Modeling & Software Development

88thth April 2005 April 2005

Bharat SalhotraBharat Salhotra

[email protected]@gmail.com

22

Transportation & IRTransportation & 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

33

ANSWERING QUESTIONS IN SEQUENTIAL ORDER IS ANSWERING QUESTIONS IN SEQUENTIAL ORDER IS NOT POSSIBLE DUE TO INTERDEPENDENCIESNOT POSSIBLE DUE TO INTERDEPENDENCIES

Interdependent variables of network planning

Solution:

Develop a DSS with three objectives

Model interdependencies at micro levels

Generalize interdependencies at Macro Level

Assess bundle of Investments based on environment

1

2

3

•Traffic /Train Mix

•Train speed differential

•Capacity of network

•Introduction of high-speed

trains•# of yards/ traction

change points

•Network quality

•Throughput

•Complexity in Route structure of freight

trains

•Quality Standards for freight traffic/ passenger

traffic

•Capacity increase of marshalling yards

•# of stops for passenger trains

•Deterioration of infrastructure

•Types of Locos/Wagons

•Market Demand

44

System Optimization

vs.

Subsystem Optimization

55

Need for LRDSSNeed for LRDSS

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

66

LRDSS: Salient FeaturesLRDSS: Salient Features

• Integrative Character: – Interdisciplinary– System wide Analysis– Simultaneous /Sequential Analysis

• Improvements in Technology/ Operating Policy• Commodity Flows • Routing Plans

77

LRDSS: Salient FeaturesLRDSS: 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

88

LRDSS : Salient FeaturesLRDSS : Salient Features

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

99

LRDSS for Decision SupportLRDSS for Decision Support

PLANNING PROCESS

Models to support different time horizons

Five Year Plans

Strategic Level

Annual Plans

Integrated LRDSS ...

BCAMDAF, FPM

FPM

1010

Broad Structure of ModelBroad Structure of Model

Traffic Assignment

Market Analysis

Traffic Forecasting

Cost Benefit Analysis

Supply AnalysisSupply Analysis

Demand Analysis

Demand Analysis

Financial Forecasting

Facility Performance

1212

Facility PerformanceFacility Performance

LINKS TERMINALS

SUPPLY SIDE

+

NETWORK

1313

Rail Performance Model Rail Performance Model Determine ability to carry trafficDetermine ability to carry traffic

LINK TYPELINK TYPE

TRAIN TYPETRAIN TYPE

CostCurve

SPEED & COST CALCULATOR

TRAFFIC

OPERATING RULE

SpeedCurve

1515

RAILS OverviewRAILS 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

1616

Train Performance CalculatorTrain 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

1717

Train Performance Train Performance CalculatorCalculator

TRAIN PERFORMANCE CALCULATOR

TRACK PROFILE

TRAIN PROFILE

LOCOMOTIVE

COACH

WAGON

RUN TIMESFuel ConsumptionSpeed Profile

1818

TPC Output (Track Profile)TPC Output (Track Profile)

1919

Train Performance Train Performance

2020

TRAIN DESPATCH TRAIN DESPATCH SIMULATORSIMULATOR

Scenario

Train Types File

Station File Run Times File

Schedule File

Special Events File

Track FileSet of Trains

Parameter File

Simulation results

2121

Train Dispatch SimulatorTrain Dispatch Simulator

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

2323

Train Dispatch SimulatorTrain 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

2424

SimulationSimulation

• 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

2525

Output from FPMOutput 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

2626

Baroda Surat Section Cost for different types of Passenger Trains

170

190

210

230

250

270

290

310

330

1 35 44 53 61 80

Trains per Day

Lo

ng

Te

rm L

ine

Ha

ul V

ari

ab

le C

os

t (

Rs

.) p

er

10

00

GT

KM

Shatabdi

SlowPassenger

Rajdhani

MailExpress

CONVERSIONINTO COST FUNCTION

2828

Market AnalysisMarket Analysis and and

Traffic ForecastTraffic Forecast

DEMAND SIDE MODELING

2929

Mode Share:Mode Share: Key DeterminantsKey Determinants(from SURVEY)(from SURVEY)

• Volumes • High volumes (>1 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

3030

Key Factors to SuccessKey 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

3131

Market Share AnalysisMarket Share Analysis

3232

Traffic Forecasting ModuleTraffic 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

3333

Traffic Analysis ZonesTraffic Analysis Zones

3434

MethodologyMethodology

• 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.

3535

# OF TAZs/TERMINALS REPRESENTED BY TYPE

TAZ/TERMINAL TYPE NUMBERFertilizer Plants 79Thermal Power Plants 41Refineries/Specialized Oil Sidings 357Iron ore/Limestone loading points for steel plants 57Coal Depots/Sidings 113Cement Plants 134Steel Plants 42Foodgrain Loading Points 284Iron Ore Loading points for Export 15Non Specialized Terminals/Goodsheds 433

Total 1555

Note: Total number of terminals exceed TAZs (746) due to double

counting w here there is more than one terminal in a TAZ.

Source: LRDSS commodity forecast Analysis

3636

Traffic Assignment ModuleTraffic Assignment Module

DEMAND + SUPPLYMODELING

3737

TrafficTraffic AssignmentAssignment ModuleModule

• Operation Research based Freight Network Equilibrium Model.

• Objective function: Minimize total cost of carrying traffic– Assign OD flows on paths using least impedance.

• (= Σ 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.

3838

Traffic Assignment ModuleTraffic Assignment Module

• Basic Inputs to the Model:– I : Demand Side

• Existing and Future Traffic– Commodity wise flows between pairs of points– Traffic for 2001’02, 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

3939

Network DatabasesNetwork 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.

4040

Attributes of a SectionAttributes of a Section

4141

Methodology for AssignmentMethodology for Assignment

• Base Year: Assignment on Preferred Paths

• Future Years: – Assignment on both Preferred & Shortest

Paths– Assignment with committed works

• Sequential/Simultaneous

4242

Analysis of TAM ResultsAnalysis 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.

4545

Variables HandledVariables 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

4646

TAM-Conceptual designTAM-Conceptual design

• Replicate Shipper’s Behavior– What commodity from where to where?

• Replicate Carriers Behavior– What commodity, what route, what train type

• Non Linear Programming Optimization Solver– MINOS

4747

Sub Modules of TAMSub 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

4848

• 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.

Sub Modules of TAMSub Modules of TAM

4949

GIS & LRDSSGIS & 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

5050

Path Editor to display/define routesPath Editor to display/define routes

5151

Path EditorPath Editor

5353

Cost Benefit Analysis & Cost Benefit Analysis & Investment PlanningInvestment Planning

5454

Utility of LRDSSUtility 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.

5555

Phase IIIPhase III

• Strengthen existing model with – Terminal Analysis– Multi-Modal Traffic Analysis– Benchmarking Operations

• Improve Information availability on desktop of decision-makers

• Interconnect

5656

Terminal Analysis ModuleTerminal 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

5757

Stylized DiagramsStylized Diagrams

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

5858

Facilities Database 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

5959

Trains Database 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

6161

Tuglakabad Terminal

R&DCONCOR

DNRCV

DNCLAS

SDNDEPT

UPDEPT

UPCLAS

S UPRCV

BTPPSUPP

DAIRY

BALLAST

DIESEL

ICDCONCOR

ELECTRIC

MINERAL

SAIL

TATA

DCD

BTPP

PFINT

NX-CR

NX-DA

TKDTKD

6262

SimulationSimulation

• 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

6363

Model OutputsModel 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

6464

Traffic Growth Rate by Commodity & OD

Freight Flows in Corridor

Mode Split Model

Target Year Total Flows

Qualitative Preference data

Target Year Rail Container Flows

Operational Statistics

Infrastructure Requirements

Cost Benefit Analysis

Multimodal Corridor Analysis ModelMultimodal Corridor Analysis Model

6565

Mode Split ModelMode Split Model

• Parameters– Price– Transit Time– Service Quality Index (Reliability, Availability,

Frequency, Loss & Damage)– Product Suitability

• Form– Cobb Douglas

6666

Multimodal Corridor Analysis ModelMultimodal 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

6767

Resource RequirementsResource Requirements

• Terminal Resources – Land– Rail Lines– Equipment (stackers, trailers, gantry cranes)– Gates– C&W

• Rolling Stock

6868

Scenario AnalysisScenario Analysis

• Assess different Investment alternatives– Do minimum (only soft changes)– De-Bottlenecking– Full Fledged Corridor

• Assess Pricing Strategies

• Assess Impact of Service Levels

6969

Interconnect-LRDSS & Other IR Interconnect-LRDSS & Other IR DatabasesDatabases

MIS(annual

summariese.g. Traffic)

FOIS(annual

summariese.g. op. stats)

Planning Data(Project Data)

Engineering Data

(Improvementsand Unit Costs)Railway Board/

LRDSSDatabases(Scenario

Data)Financial

Data(e.g. budgets)

Zonal Railway Data(Line and Section Data)

7070

LRDSSData

Storage

Intranet

Tape Storage

LRDSS ClientLRDSS ClientLRDSS Client

LRDSS Client LRDSS Client

LRDSS ClientCDROM Reader

CDROM Reader

GIS/Trans E-mail and FTP Site

ScannerPlotter

IR Web Page

CDWORMWriter

CDROMReader

CDROMReader

CDROMReader

LRDSS Site Componentto be Acquired

Componentto be Deleted

v

RAILSSimulation

Module

LRDSS MDV Clients

CDROMReader

LRDSS LAN

Current LRDSS Architecture

v

7171

LRDSSData

Storage(Oracle)

Internet


LRDSS Client LRDSS Client

LRDSS MDV Client

CDROM Reader

ScannerPlotter

CDWORMWriter

CDROM Reader CDROM Reader CDROM Reader

Pilot LRDSS Clientat Zonal Railway

CDROM Reader

CDROM Reader

RAILSSimulation

Module

RAILSSimulation

Module

BCAMlite

Railway Board LAN

LRDSS MDV Clients

OtherIR

Databases(FOIS, TMS,

MIS)

Proposed Short Term LRDSS Architecture

7272

LRDSSData

Storage(Oracle+

SDE)

Internetor WAN


LRDSS MDV Client LRDSS Client(Expert User)

LRDSS MDV Client

CDWORMWriter

LRDSS Clientsat Zonal Railways

RAILSSimulation

Module

RAILSSimulation

Module

GIS/Trans E-mail and FTP Site

IR Web Page

IR FTP Site

LRDSS MDV Clients

MoreMDV

Clients

with CDROM Readers

LRDSS Unit

LRDSS MDV Clients

OtherIR

Databases(MIS+FOIS+

Planning)

Other ZonalRailways

OtherZonal

RailwaysDatabases(incl. GIS)

RAILSSimulation

Module

BCAMlite

BCAMlite

RAILSSimulation

Module

Railway Board LAN

Proposed Medium Term Architecture (1 ½ - 3 years)

7373

KEY AREAS FOR KEY AREAS FOR COLLABORATIONCOLLABORATION

• LINE CAPACITY SIMULATOR

• TRAFFIC ASSIGNMENT MODEL– PATH GENERATOR– OPTIMIZATION ALGORITHM

• PASSENGER TERMINAL DESIGN

7474

THANK YOUTHANK YOU

1 long range decision support system - design overview - institutional knowledge -issues unresolved...

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