Coupling Genetic Local Search and Recovering Beam Search algorithms for minimizing the total completion time in the single machine scheduling problem subject to release dates - Rakrouki, Mohamed Ali; Ladhari, Talel; T’kindt, Vincent (Computers & operations research, 2012)
In this paper we consider the well-known single machine scheduling problem with release dates and minimization of the total job completion time. For solving this problem, denoted by 1 | r j | ∑ C j , we provide a new metaheuristic which is an extension of the so-called filtered beam search proposed by Ow and Morton [30]. This metaheuristic, referred to as a Genetic Recovering Beam Search (GRBS), takes advantages of a Genetic Local Search (GLS) algorithm and a Recovering Beam Search (RBS) in order to efficiently explore the solution space. In this paper we present the GRBS framework and its application to the 1 | r j | ∑ C j problem. Computational results show that it consistently yields optimal or near-optimal solutions and that it provides interesting results by comparison to GLS and RBS algorithms. Moreover, these results highlight that the proposed algorithm outperforms the state-of-the-art heuristics.