In this and a companion paper a dynamic programming (DP) approach to solve a smart home appliances scheduling problem is considered. The challenge with solving the scheduling problem is the coupling of decision variables due to some time precedence constraints. In general, the system of precedence constraints may contain redundant constraints that offer opportunities for simplification. This simplification is desirable for reducing the computation effort of the nonserial DP procedure presented in the companion paper (i.e., Part II). The current paper establishes the uniqueness of the maximum set of redundant constraints and its polynomial-time solvability with optimality guarantee, under the sufficient and necessary condition that the precedence graph (a graph representation of the precedence constraints system) does not contain any cycle with nonnegative weight. A numerical case study indicates the efficiency of the proposed simplification algorithm versus the brute-force enumerative search. Besides helping to reduce the computation effort in the DP procedure described in the companion paper, the algorithm in the current paper solves a generalization of a precedence graph simplification problem arising from application areas such as parallel computing.