LT Catherine Long LT James Koffi

 Background  Problem/Model Scenario  Network Model  Interdiction  Takeaways/Further Research  Summary/Conclusions  Recommendations

 Greyhound serves more than 3,800 destinations in North America and employs around 7,800 staff.  Greyhound operated nearly 5.5 billion passenger miles last year.  The U.S. operation, as well as its operating subsidiaries and Greyhound Canada, carried nearly 18 million people.

 Intercity bus is the safest mode of transportation over cars, trucks, trains, planes and other commercial vehicles, according to the U.S. Department of Transportation  The Greyhound active fleet consists of about 1,775 buses, with an average age of 9.4 years.  One Greyhound bus takes an average of 19 cars off the road, and achieves 170 passenger miles per gallon of fuel.

 YouTube Video  Ie8T0&feature=channel&list=UL Ie8T0&feature=channel&list=UL

 The price of gas is expensive, and routes between stations vary throughout the state  New buses save gas and will keep up with the competition (Mega Bus, etc.)  What is the fastest and most cost effective way to transition 50 new express buses from two major Greyhound stations to other stations around the state of California?

 Model distributes 50 new buses throughout CA  Use GAMS to model the flow of buses to new stations and demonstrate how an “attack,” such as a major earthquake, impacts the network  The “attacks” model the worst case scenario and completely disable edge

 The nodes in model represent stations  The arcs represent routes from one station to another  Route information is from the Greyhound website  Supply nodes are Oakland and Los Angeles

Road Map of California

Network Model S T

S Oakland Los Angeles T Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

 The measure of effectiveness (MOE) for this model is to minimize the total cost of the flow of buses to their destination cities  Cost = $/gallon x miles per edge  Each city besides the supply cities receives 2 brand new buses

 Assume all new Greyhound buses get 6.5 miles per gallon  Cost per gallon of diesel is $4.00  Edge capacities are never exceeded in our model

 Many cities are connected by narrow two way roads which are prohibited for use by Greyhound or any bus/motorhome in CA due to handling issues.  Bus: California Vehicle Code (CVC) Section 233 defines "bus" as: "(a) …any vehicle… …designed, used, or maintained for carrying more than 15 persons including the driver”California Vehicle Code (CVC) Section 233”  This is one of the major limitations to the network.

 The model is run without interdiction to establish a baseline total minimum cost of $3,  Run the model with increasing attacks to determine network resiliency  GAMS chooses routes that will maximize the total cost after each “attack”

Network Model With 1 Attack S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 2 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 3 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 4 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 5 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 6 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 7 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 8 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 9 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 10 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 11 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 12 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

 Can model resiliency be improved with an additional supply node in Bakersfield?  Yes, but it only changes the model slightly…

Network Model With 1 Attack S Oakland Los Angeles T Cost = buses unable to reach Oceanside and San Diego Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 2 Attacks S Oakland Los Angeles T Cost = buses unable to reach Oceanside and San Diego Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 3 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 4 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 5 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 6 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 7 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 8 Attacks S Oakland Los Angeles T Cost = buses unable to destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 9 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 10 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 11 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 12 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 13 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 14 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

 The most costly “attacks” occur with the first attack and the fourth attack  Attack #1: , = $  Attack #4: = $

Network Model With 1 Attack S Oakland Los Angeles T Cost = Difference , = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 3 Attacks S Oakland Los Angeles T Cost = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

Network Model With 4 Attacks S Oakland Los Angeles T Cost = Difference = = buses unable to reach destination Santa Rosa Santa Cruz San Francisco Santa Maria San Luis Obispo King City Salinas Stockton San Diego Indio Sacramento Vallejo Modesto Merced Fresno Bakersfield Palmdale Oceanside Victorville Indio Riverside Oxnard Coalinga Jct Los Banos Santa Jose

 The additional supply station in Bakersfield decreased overall cost by $1, after 14 attacks  In the scenario with 3 supply stations Bakersfield started out by supplying just 4 new buses  By the 14 th attack, Bakersfield supplies 14 buses  The more supply nodes the better, however may not be cost effective for Greyhound to have so many bus contracts

 Change the probability of destruction based on location, i.e. if on a fault line  Additional routes could be added to local roads and streets that connect the major interstates to build more redundancy in the network, but must abide to California state laws

 Model improvements can be achieved by increasing the granularity of the model  Can adapt the model to include other costs  Price-tiered system  Discounts on certain routes  Express routes

 We conclude there is not enough resiliency in the Greyhound network to sustain affordable bus transition operations in the event of “attacks” on the network depending on budget  Model can be used as a tool to weigh cost benefits of going around edges caused by a major traffic accident, or waiting an additional day for it to clear

  greyhound-express greyhound-express