Computational Progress in Linear and Mixed Integer Programming

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Customer Applications (2012 Gurobi Sales – 200+ new customers) ▸ Accounting ▸ National research labs ▸ Advertising ▸ Online dating ▸ Agriculture ▸ Portfolio management ▸ Airlines ▸ Railways ▸ ATM provisioning ▸ Recycling ▸ Compilers ▸ Revenue management ▸ Defense ▸ Semiconductor ▸ Electrical power ▸ Shipping ▸ Energy ▸ Social networking ▸ Finance ▸ Sourcing ▸ Food service ▸ Sports betting ▸ Forestry ▸ Sports scheduling ▸ Gas distribution ▸ Statistics ▸ Government ▸ Steel Manufacturing ▸ Internet applications ▸ Telecommunications ▸ Logistics/supply chain ▸ Transportation ▸ Medical ▸ Utilities ▸ Mining ▸ Workforce Management © 2015 Gurobi Optimization 20
Solving MIPs © 2015 Gurobi Optimization 21
Page 1 and 2: Computational Progress in Linear an
Page 3 and 4: The Early History ▸ 1947 - George
Page 5 and 6: The Decade of the 80’s ▸ Mid 80
Page 7 and 8: Linear Programming © 2015 Gurobi O
Page 9 and 10: Example: A Production Planning Mode
Page 15 and 16: Progress in LP: 1988—2015 Algorit
Page 17 and 18: LP Today ▸ However, a word of war
Page 19: A Definition A mixed-integer progra
Page 23 and 24: A Bumpy Solution Landscape © 2015
Page 25 and 26: Example 2: MIP really is HARD A cus
Page 27 and 28: Example 3: A typical situation toda
Page 29 and 30: Computational History: 1950 -1998
Page 31 and 32: MIP Speedups © 2015 Gurobi Optimiz
Page 33 and 34: CPLEX Version Performance Improveme
Page 35 and 36: 1000000000 Gurobi MIP Library (3550
Page 37 and 38: MIP Solvability © 2015 Gurobi Opti
Page 39 and 40: Suppose you were given the followin

Computational Progress in Linear and Mixed Integer Programming

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