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Got Gas?

Got Gas?. Jim and Michael. Problem Statement (Weight 15%). An investigation of a gas pump queue as a function of rationing policy We modeled the queue at a gas station specifically during a gas crisis in which the number of gallons in a single purchase is limited.

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Got Gas?

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  1. Got Gas? Jim and Michael

  2. Problem Statement (Weight 15%) • An investigation of a gas pump queue as a function of rationing policy • We modeled the queue at a gas station specifically during a gas crisis in which the number of gallons in a single purchase is limited.

  3. Mathematical/Algorithmic Model (Weight 25%) • Queue length was modeled by following a decision making matrix that was created using fixed quantities for amount of gas in a tank. Later matrix was improved to use percentages since agents have varying gas tank capacities.

  4. Mathematical/Algorithmic Model (Weight 25%) - cMap

  5. Agent-Based Model (Weight 25%) • Gas Crisis 1973 • Know 2-3 hour wait • Know purchase limited to 10 gallons • Agent never join queue if tank is > 50% as per policy • Know MPG was 14 MPG • Model functions as expected

  6. Agent-Based Model (Weight 25%) • If gas crisis today – what would happen? • Know mpg = 24 (2004) • Fewer gas station • Faster checkout – pay at pump and no full-service • Based on model queue wait time would be longer at 5 gallons per fill up

  7. Agent-Based Model (Weight 25%) • Is the agent-based model a reasonable representation of the problem? • We believe that it does based on its reflection of the 1973 situation. • Does the model provide insight into the problem? • Yes, it demonstrates that improved MPG would minimize wait times. • Can anything be learned from the model? • Continued investment in improving MPG or alternates to gas purchases (public transportation alternative fuels) will continue to erode the effect of gas pump queue lines.

  8. Factors modeled Various tank sizes Various initial states Average miles per gallon Varied number of cars to fix demand Agents have various sizes of tanks Decision to join queue based on fuel state line length policy Agent-Based Model (Weight 25%) • Does the team understand the agent’s states and behaviors, and the role of the environment? In particular, does the team understand how the agents affect each other and/or modify their environment? • Used agents to generate demand and represent queue length

  9. Agent-Based Model (Weight 25%) • Assumptions • One pump • 50 miles of road • 15 cars • Decision to get in line depends on number of people in queue • Limitations • Driving habits • Option for alternative transportation

  10. Results & Conclusions (Weight 15%) - Graphs

  11. Results & Conclusions (Weight 15%) • Limiting the amount of gas per purchase did not have a significant impact until quantities were reduced to below 10 gallons. • One factor that is not modeled is anxiety. We believe that the long lines at the pump are more a result of concern about future availability at current prices.

  12. Code (Weight 10%) Globals [queue totWait totVisit ] turtles-own [gas done tanksize waittime waithold visits] to setup ca set totVisit 0 set queue 0 set gasPlus 20 ask patches [ setup-road ] setup-cars open-file end

  13. Code (Weight 10%) - This function draws the roads to setup-road ;; patch procedure if ( pycor < 4. ) and ( pycor > 1 ) [ set pcolor white ] ; upper road if ( pycor < -1 ) and ( pycor > -4 ) [ set pcolor white ] ; lower road if ( pycor = 0 ) and ( pxcor = 48 ) [set pcolor green] ; gas station if ( pycor = -4 ) and ( pxcor = 47 ) [set pcolor grey ] ; gas pump end

  14. Code (Weight 10%) - This function creates the cars to setup-cars set-default-shape turtles "car" crt numcars [ set color 10 + random 130 set visits 0 set waittime 0 set done -1 set tanksize 10 + random 12 set gas 2.5 + random 7.5 ; various amounts of gas at start setxy random 50 3 ; spreads out cars along road set heading 90 ; cars drive east set label gas ; tells how many gallons each car has separate-cars ] ; set sample-car one-of turtles ; ask sample-car [ set color red ] end

  15. Code (Weight 10%) - This function spreads the cars out ; this function is needed so when we click "Setup" we ; don't end up with any two cars on the same patch to separate-cars ;; turtle procedure if any? other turtles-here [ fd 1 ; 1 separate-cars ] end ; this function is needed so when we click "go" we ; don't end up with any two cars on the same patch to separate-queque ;; turtle procedure if any? other turtles-here [ bk 1 separate-queque ] end

  16. Code (Weight 10%) - This function is an envelope for the loop to master start if gasPlus < 5 [ printout file-close stop] end

  17. Code (Weight 10%) - This function runs each iteration to start tick ask turtles [go] if totvisit > 0 [ plot (totwait / totvisit) ] if ticks > 2500 [ printout type gasPlus type " " print (totwait / totvisit) set gasPlus gasPlus - 1 reset-ticks set totvisit 0 set totwait 0 ] end

  18. Code (Weight 10%) - Allows cars to know if they are in line to Go ifelse ([pcolor] of (patch-at 1 3)) = 55 ; Am at the pump? [ ;Yes I am set done (done + 1) if done > 9 [ ; I’m done I need to leave the pump>> setxy 49 3 set done 0 set gas (gas + gasplus) set queue (queue - 1) set totwait totwait + (waittime - waithold) set totvisit totvisit + 1 if gas > tanksize [set gas tanksize ] ;don't overflow tank ] ] [ ; I am not at the pump if ycor = -3 [set waittime (waittime + 1) ] fd 1 if any? other turtles-here [bk 1] ]

  19. Code (Weight 10%) - Continuation of Go for cars on road ifelse ( ([pcolor] of patch-at 1 -3) = 55 ) ;is the gas station close? [ shouldI ] [ move ] end

  20. Code (Weight 10%) - Moves cars if they are driving – using gas to move if gas > 0 [ if ycor != -3 [fd 1 set gas (gas - ( factor / mipg ))] ;move consuming gas ;show (sentence precision gas 2 tanksize precision (gas / tanksize) 2 waittime totwait totvisit ) ;tell us percent of gas left in tank ] end

  21. Code (Weight 10%) - THE MATRIX to shouldI ifelse ( gas / tanksize ) > .5 [move] [ ifelse ( gas / tanksize ) > .25 and queue > 5 [move] [ ifelse gas > 2.5 and queue > 10 [move] [getInLine] ] ] end

  22. Code (Weight 10%) - Moves cars to Queue to getInLine set visits (visits + 1) set waithold waittime setxy 40 -3 ; move to the queue road set queue (queue + 1) ; increase the queue count separate-queque ; keeps cars seperate in line end

  23. Code (Weight 10%) - Creates a CSV file and creates headers to open-file let file "output1.csv" ;user-new-file if ( file != false ) [ if ( file-exists? file ) [ file-delete file ] file-open file ] file-print (word "Gas Plus,Number of Cars,Wait time,Visits,Average") end

  24. Code (Weight 10%) - Adds data to CSV file for each iteration to printout let average (totWait / (totVisit + .000001) ) ; file-print (word "Gas Plus,Number of Cars,Wait time,Visits,Average") file-print (word gasPlus "," numcars ","totWait","totVisit "," average ) ; end

  25. Code (Weight 10%) - Sample CSV file

  26. Code (Weight 10%) - Real-time demo Got Gas-G.nlogo

  27. Display (Weight 10%) We recognize that time is limited and we may have skipped something, so we would like to take this opportunity to ask if there are any questions or parts of the presentation that need to be repeated?

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