New resource-constrained project scheduling instances for testing (meta-)heuristic scheduling algorithms

The resource-constrained project scheduling problem (RCPSP) is a well-known that has attracted attention since several decades. Despite the rapid progress of exact and (meta-)heuristic procedures, can still not be solved to optimality for many instances relatively small size. Due known complexity, researchers have proposed fast efficient meta-heuristic solution procedures solve near optimality. excellent results obtained in last decades, little why some heuristics perform better than others. However, if understood generate good solutions while falling short others, this could lead insights improve these meta-heuristics, ultimately leading stronger algorithms overall quality. In study, new hardness indicator measure difficulty providing near-optimal procedures. based on concept uses ? distance metric describe space instance, relies current knowledge lower upper bound calculations from five datasets literature. This indicator, which will called ?D used only existing datasets, but also benchmark dataset future research purposes. contains with different values it shown value actually describes through two