The authors introduce functions F defined in Rn and feasible sets S of integral n-vectors having the property that the problem of optimizing F over S can be solved by the Greedy Algorithm. This framework includes many non-linear optimization models arising from different fields of application, such as scheduling, resource allocation, assignment of facilities to task, etc. The authors discuss the problem of representing S as the set of integral solutions of a linear system of inequalities.
