RAS - TAU - (RAS November7,2010 Team:TAUIE Mor Kaspi...

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Railway Application Section (RAS) Problem Solving Competition November 7, 2010 am: TAU Team: TAU IE Mor Kaspi and Tal Raviv*, Tel Aviv University, Israel
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lution Method Solution Method MILP formulation + Specialized cuts d and Domination rules Commercial Solver 2
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uality of results obtained Quality of results obtained Solution value: 11,399,670.88$ Absolute optimality gap: 0.30$ elative gap: 3 (Relative gap: 2.63E 8) Best known solution and 0.01% gap found in less than five minutes 3
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IP Formulation MIP Formulation Subject to
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uts Cuts No Contract > No Fueling Fixed Cost 5
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uts Cuts Stops Subsequences inequalities 1000 2000 1000 1000 1000 0 2 3 1 5 4 L ocomotive T ank V olume = 4500 4500 gallons 6
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uts Cuts Yards Subsequences Inequalties 1000 2000 1000 1000 1000 2 4 1 3 3 1 y 2 + y 3 + y 4 1 y 3 + y 4 1 7
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uts Cuts Minimal number of fuels per locomotive A tight lower bound can be calculated in polynomial time by casting each locomotive problem as shortest path problem 8 TR1
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Slide 8 TR1 אמגוד Tal Raviv, 24/10/2010
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uts Cuts Enough Fuel To Reach the Next Station 9
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uts Cuts Locomotive decomposition 10
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This note was uploaded on 11/06/2011 for the course ISE 421 taught by Professor Km during the Spring '11 term at King Fahd University of Petroleum & Minerals.

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RAS - TAU - (RAS November7,2010 Team:TAUIE Mor Kaspi...

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