Maximizing throughput of jobs with multiple resource requirements

We consider the problem of scheduling jobs that require multiple resources such as memory, bandwidth and processors. For each job, the input specifies start time, finish time and profit; the input also specifies the job´s requirement for each resource. Each resource has a fixed capacity (called bandwidth). A feasible solution is a subset of jobs such that for any timeslot and any resource, the total requirement of the jobs active at the timeslot does not exceed the capacity of the resource. The goal is to maximize the profit of the jobs selected. We present an approximation algorithm with provable guarantees and effective heuristics for this problem. The algorithm has an approximation ratio of O(r), where r is the number of resources. We present an experimental evaluation of our algorithms that exhibit their effectiveness.