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Telecommunication problems Description
Further explanation of this example:
'Applications of optimization with Xpress-MP', Chapter 12: Telecommunication problems
Source Files By clicking on a file name, a preview is opened at the bottom of this page.
Data Files
g6transmit.mos (!****************************************************** Mosel Example Problems ====================== file g6transmit.mos ``````````````````` Placing mobile phone transmitters A mobile phone operator plans to equip a currently uncovered region. There are 7 possible locations for the transmitters. Each site has a defined number of communities it can serve. Given the construction cost and reach of each site, where should the transmitters be built so that the largest population is covered with the given budget restrictions? The formulation as a covering problem is straightforward. We store data for 'COVER' in sparse format, that is, only the entries with value 1 are given. Since this array is declared as a dense array, all other entries are automatically populated with value 0. (c) 2008-2022 Fair Isaac Corporation author: S. Heipcke, Apr. 2002, rev. Mar. 2022 *******************************************************!) model "G-6 Transmitter placement" uses "mmxprs" declarations COMMS = 1..15 ! Set of communities PLACES = 1..7 ! Set of possible transm. locations COST: array(PLACES) of real ! Cost of constructing transmitters COVER: array(PLACES,COMMS) of integer ! Coverage by transmitter locations POP: array(COMMS) of integer ! Number of inhabitants (in 1000) BUDGET: integer ! Budget limit build: array(PLACES) of mpvar ! 1 if transmitter built, 0 otherwise covered: array(COMMS) of mpvar ! 1 if community covered, 0 otherwise end-declarations initializations from 'g6transmit.dat' COST COVER POP BUDGET end-initializations ! Objective: total population covered Coverage:= sum(c in COMMS) POP(c)*covered(c) ! Towns covered forall(c in COMMS) sum(p in PLACES) COVER(p,c)*build(p) >= covered(c) ! Budget limit sum(p in PLACES) COST(p)*build(p) <= BUDGET forall(p in PLACES) build(p) is_binary forall(c in COMMS) covered(c) is_binary ! Solve the problem maximize(Coverage) ! Solution printing writeln("Total coverage: ", getobjval, " (of ", sum(c in COMMS) POP(c), ") total cost: ", getsol(sum(p in PLACES) COST(p)*build(p))) write("Build transmitters:") forall(p in PLACES | getsol(build(p))>0) write(" ", p) write("\nCommunities covered:") forall(c in COMMS | getsol(covered(c))>0) write(" ", c) writeln end-model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

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