root/OptimizingMATLABCode/CellTower/PhoneTowerScript.m @ 11
| 10 | anderm8 | %% Demo script for Cell Tower Optimization Problem
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% This demo illustrates how you would set up and solve an optimization
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% problem (constrained non-linear minimization).
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%
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% The problem is to determine the locations of # cell towers, each having
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% various coverage radius, so that there is maximum coverage, or minimum
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% overlap. It is a constrained optimization problem because the cell towers
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% are constrained to lie within a boundary. It is a non-linear optimization
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% problem because of the non-linear objective function (overlap area as a
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% function of # cell tower locations).
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%
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% The demo is designed to show the key steps in setting up and solving an
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% optimization problem. The details of the problem can be omitted by using
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% predefined objective and plotting functions.
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% Copyright 2015 The MathWorks, Inc.
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%% Define parameters
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towers = 40; % number of towers
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side = 15; % dimension of piece of land (one side)
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seed = 5; % seed for random initial condition (not relavent to optimization
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% Shutting down the pool in case one is accidentially left open
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p = gcp('nocreate');
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if ~isempty(p)
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delete(gcp)
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end
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%% Define initial conditions
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% |celltowersetup.m| sets up the initial conditions:
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%
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% dimensions.R : radius of cell tower coverage
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% dimensions.xL : 0 % for plotting
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% dimensions.xU : side % for plotting
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% dimensions.yL : 0 % for plotting
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% dimensions.yU : side % for plotting
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% lb : lower bound values for x, y (based on the radius)
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% ub : upper bound values for x, y (based on the radius)
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% x0 : initial center points (x, y pairs)
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[dimensions,lb,ub,x0] = helper.celltowersetup(towers,side,seed);
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%% Run the following optimization
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tic
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[x,fval,exitflag,output] = helper.myOptim(x0,lb,ub,dimensions); %#ok<ASGLU>
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t1 = toc;
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fprintf('Elapsed time is %0.2f seconds.\n', t1);
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%% Run with Pool
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% Open pool of workers. Re-run the optimization routine to see the speedup.
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% Pool will open by default, to manually open a pool...
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p = parpool(2); % open pool
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parallel = 1; % set to 1 to trigger 'useparallel','always'
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tic
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[x,fval,exitflag,output] = helper.myOptim(x0,lb,ub,dimensions,parallel);
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t2 = toc;
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fprintf('Elapsed time is %0.2f seconds.\n', t2);
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%% Summary visualization
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% If you added the custom output function |myOutputFcn| in Optim GUI, you
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% can get a summary visualization:
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helper.plotOptimSummary(output,dimensions);
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fprintf('Speed up (time serial / time parallel): %0.2f\n', t1/t2);
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%% Close Pool
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delete(p)
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