The Disjunctive Temporal Problem (DTP) involves the satisfaction of aset of constraints represented by disjunctive formulas of the form x 1 - y 1 <= r 1 or x 2 - y 2 <= r 2 or ... or x k - y k <= r k . DTP is a  general temporal reasoning problem which includes the well-known Temporal Constraint Satisfaction Problem (TCSP) introduced by Dechter, Meiri and Pearl. This paper describes a basic constraint satisfaction algorithm where several aspects of the current literature are integrated, in particular the so-called incremental forward checking.  Hence,two new extended solving strategies are proposed and experimentally evaluated. The new proposed strategies are very competitive with the best results available in the current literature. In addition, the analysis of the empirical results suggests future research directions concerning in particular the use of arc-consistency filtering strategies.

This paper proposes an iterative improvement approach for solving the Resource Constraint Project Scheduling Problem with Time-Windows (RCPSP/max), a well-known and challenging NP-hard scheduling problem. The algorithm is based on Iterative Flattening Search (IFS), an effective heuristic strategy for solving multi-capacity optimization scheduling problems. Given an initial solution, IFS iteratively performs two-steps: a relaxation-step , that randomly removes a subset of solution constraints and a solving-step , that incrementally recomputes a new solution. At the end, the best solution found is returned. The main contribution of this paper is the extension to RCPSP/max of the IFS optimization procedures developed for solving scheduling problems without time-windows. An experimental evaluation performed on medium-large size and web-available benchmark sets confirms the effectiveness of the proposed procedures. In particular, we have improved the average quality w.r.t. the current bests, while discovering three new optimal solutions, thus demonstrating the general efficacy of IFS.