It is a well-known fact that there exists an ever increasing number of problems for which,despite the efforts of many inventive and persistent researchers, it seems virtually impossible to find efficient algorithms. In this situation, the theory of computational complexity may provide helpful...

Most scheduling problems are notoriously intractable, so the majority of algorithms for them are heuristic in nature. Priority rule-based methods still constitute the most important class of these heuristics. Of these, in turn, parameterized biased random sampling methods have attracted...

Most scheduling problems are notoriously intractable, so the majority of algorithms for them are heuristic in nature. Priority rule-based methods still constitute the most important class of these heuristics. Of these, in turn, parameterized biased random sampling methods have attracted...

It is well-known that for many project scheduling problems the Space AS of active schedules contains at least one optimal solution for each feasible instance, so restricting heuristic construction methods to AS will improve algorithmic efficiency without foresaking the chance to eventually find...

For most computationally intractable problems there exists no heuristic that is equally effective on all instances. Rather, any given heuristic may do well on some instances but will do worse on others. Indeed, even the 'best' heuristics will be dominated by others on at least some subclasses of...