New summary measures and datasets for the multi-project scheduling problem

In recent years, more researchers have devoted their attention to the resource-constrained multi-project scheduling problem, resulting in a growing body of knowledge on solution procedures. A key factor comparison these procedures is availability benchmark datasets that cover large part feature space. Otherwise, one risks conclusions from experiments sets do not hold when they are repeated different set. this paper we propose new contain instances with wide variety characteristics. We first develop several summary measures describe three types portfolio characteristics, two present any existing datasets. Second, an algorithm developed can generate desired parameter values controlled manner. With procedure, create each focus characteristics and fourth dataset contains all combinations. The computational results show (a) significantly larger space than libraries (b) challenging for advanced algorithms.