56 lines
2.0 KiB
Mathematica
56 lines
2.0 KiB
Mathematica
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function [p,feasible] = boxreduce(p,upper,lower,lpsolver,options,xmin);
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if options.bmibnb.lpreduce
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improvethese = zeros(length(p.c),1);
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improvethese(p.linears) = 1;
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vol_start = prod(p.ub(p.branch_variables)-p.lb(p.branch_variables));
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diag_before = sum(p.ub(p.branch_variables)-p.lb(p.branch_variables));
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span_before = p.ub - p.lb;
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[pcut,feasible,lower] = lpbmitighten(p,lower,upper,lpsolver,xmin,improvethese);
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p.counter = pcut.counter;
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diag_after = sum(pcut.ub(p.branch_variables)-pcut.lb(p.branch_variables));
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span_after = pcut.ub - pcut.lb;
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% Variables with gap smaller than desired precision is no longer bound
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% propagated
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improvethese(find(abs(span_after) <= p.options.bmibnb.vartol)) = 0;
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not_decreasing = find(span_after >= 0.8*span_before);
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improvethese(not_decreasing) = max(0,improvethese(not_decreasing)-1);
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iterations = 0;
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% while (diag_after/(1e-18+diag_before) < .75) & feasible & iterations < 4
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while any(improvethese) & feasible & iterations < 8
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span_before = span_after;
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[pcut,feasible,lower] = lpbmitighten(pcut,lower,upper,lpsolver,xmin,improvethese);
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p.counter = pcut.counter;
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span_after = pcut.ub - pcut.lb;
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improvethese(find(abs(span_after) <= p.options.bmibnb.vartol)) = 0;
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not_decreasing = find(span_after >= 0.95*span_before);
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improvethese(not_decreasing) = max(0,improvethese(not_decreasing)-1);
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%diag_before = diag_after;
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%diag_after = sum(pcut.ub(p.branch_variables)-pcut.lb(p.branch_variables));
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iterations = iterations + 1;
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end
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% Clean up...
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for i = 1:length(pcut.lb)
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if (pcut.lb(i)>pcut.ub(i)) & (pcut.lb-pcut.ub < 1e-3)
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pcut.lb(i)=pcut.ub(i);
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pcut = updatemonomialbounds(pcut);
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end
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end
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p.lb = pcut.lb;
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p.ub = pcut.ub;
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p.lb(p.lb<-1e12) = -inf;
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p.ub(p.ub>1e12) = inf;
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p.evalMap = pcut.evalMap;
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else
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feasible = 1;
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end
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