 Weighted interval scheduling

Weighted interval scheduling assigns each job a reward $w_i$ and maximizes their sum over compatible jobs. Earliest finish can fail for this different objective function; dynamic programming can compare alternatives.^[ref]

For a separate two-job example, let $X=[0,2)$ have reward one and $Y=[1,3)$ reward ten. Earliest finish accepts $X$ and rejects $Y$, earning one; the optimum accepts $Y$, earning ten. Replacing $Y$ by $X$ preserves job count but loses reward. Thus the interval scheduling exchange argument proves the unit-value theorem only: its preserved quantity must match the intended objective function.