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@@ -1131,8 +1131,8 @@ dependencies into account. It must be understood that the linear programming
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problem size is quadratic with the number of tasks and thus the time to solve it
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will be very long, it could be minutes for just a few dozen tasks. You should
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probably use @code{lp_solve} to convert the problem to MPS format and then
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-use a better solver, @code{glpsol} is already better than @code{lp_solve} for
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-instance (the @code{--pcost} option may be useful). Setting @code{deps}
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+use a better solver, @code{glpsol} might be better than @code{lp_solve} for
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+instance (the @code{--pcost} option may be useful), but sometimes doesn't manage to converge. Be sure to try all the @code{-B} options of @code{lp_solve}. Setting @code{deps}
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to 0 will only take into account the actual computations on processing
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units. It however still properly takes into account the varying performances of
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kernels and processing units, which is quite more accurate than just comparing
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