We are given a path with a demand on each edge and a set of tasks, each task being defined by a subpath and a size. The goal is to select a subset of the tasks of minimum cardinality such that on each edge e the total size of the selected tasks using e is at least the demand of e.
There is a polynomial time 4-approximation for the problem [Bar-Noy et al., STOC 2000] and also a QPTAS [Höhn et al., ICALP 2014].
In this paper we study fixed-parameter algorithms for the problem.
We show that it is W[1]-hard but it becomes FPT if we can slighly violate the edge demands (resource augmentation) and also if there are at most k different task sizes.
Then we present a parameterized approximation scheme (PAS), i.e., an algorithm with a running time of f(k)n^{O_{\epsilon}(1)} that outputs a solution with at most (1+\epsilon)k tasks or assert that there is no solution with at most k tasks.
In this algorithm we use a new trick that intuitively allows us to pretend that we can select tasks from OPT multiple times.
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