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Heuristics and metaheuristics for a parallel machine scheduling problem: a computational evaluation

In scheduling theory, minimizing the weighted number of late jobs in the general case (non-equal release dates) is an objective function usually used as a performance indicator. This paper presents several approaches for the NP-Hard parallel machine scheduling problem, including two MILP formulations for exact resolution and various heuristics and metaheuristics to solve large size instances. An original data structure is developed and allows flexibility for computing starting times once the sequence is fixed. A simple neighborhood combined with this data 1 structure is used in the heuristics and metaheuristics and give promising results.