Heuristic algorithms for solving a set of NP-hard single-machine scheduling problems with resource-dependent processing times

In this paper we study a large set of single-machine scheduling problems with resource-dependent processing times that reduce (consolidate) to the same mathematical model. We take advantage of this property to present a set of universal (unified) heuristic algorithms capable of solving any of the problems that reduces to the unified model. By performing an extensive experimental study, we show that the suggested heuristics can solve large instances of this set of problems with a negligible average percent relative gap between the value of the heuristic solution and the value of a tight lower bound on the optimal solution value.