Decomposition algorithm for resource-constrained multi-project scheduling problem

In order to address the multi-objective optimization of resource-constrained multi-project scheduling problem (RCMPSP), a two-stage decomposition algorithm based on hierarchical decomposing strategy was proposed to orderly tackle their precedence constraints and resource constraints in an integrated framework. Furthermore, the solving procedure of RCMPSP was presented, structured by two stages. In the first stage of precedence constraints satisfactory optimization stage, a revised ant colony optimization (ACO) was presented to obtain the feasible activity sequence. In order to accelerate the convergence efficiency and quality, a revised pheromone increment updating operator of ACO with combination of parallel schedule generation scheme (PSGS) were used. During the process constructing feasible precedence activity sequence, a sequencing indicator was presented to solve the constraint conflict resolution problem when some parallel activities competed some resources simultaneously. Specifically, the TOPSIS based on entropy weight and multi-attribute decision making based on ordered weighted averaging (OWA) operator was used to obtain the integrated importance measure of activity as the indicator. At the second stage of resource-constraints satisfactory optimization stage, the obtained optimum precedence activity sequence was taken as the stage's input, and the resource capacity was examined and adjusted one by one until the optimal scheduling solution was obtained. The results illustrated the effectiveness of the proposed two-stage decomposition algorithm for RCMPSP.