Effective GRASP for the Dynamic Resource-Constrained Task Scheduling Problem

The Task Scheduling Problem is subject of many studies in Network Optimization due to its applicability in many areas of engineering and computation. There are many models of environments (homogeneous/heterogeneous), constraints (communications costs, use of resources [i]) and many objectives (reduction of makespan/processor idleness) that can be applied to simulate a real problem. This work analyzes a new modeling that differs from previous ones, because the tasks have a new entity: a profit. After the activation of a task, it generates an amount of resources that must be used to activate other tasks. Therefore, the resource handling is very dynamic because it is not possible (a priori) to define how many resources will be available at each time. This problem, proposed in [iii], is called Dynamic Resource-Constrained Task Scheduling Problem (DRCTSP).