Abstract
In this article the application of the discrete version of the bat algorithm to flowshop scheduling problems is presented and compared with Simulated Annealing, Local Search, as well as versions of each that start from constructive heuristics (Palmer and CDS). Bat algorithm is a novel metaheuristic, developed for continuous problems that has shown exceptional results. This paper intends to assess its effectiveness and efficiency for discrete problems when compared with other optimization techniques, including Simulated Annealing and Local Search, whose results are already proven. First, it was developed a literature review about those algorithms, then they were implemented in VBA with Microsoft Excel. Once implemented, the parameterization was carried out, ensuring an adequate application of the algorithms before they can be compared. Then, the methods were applied for 30 normally distributed instances, in order to draw broader conclusions. Finally, a statistical evaluation was carried out and concluded the inferiority of the Local Search in relation to the metaheuristics and the superiority of the hybrid version of the Bat Algorithm with CDS in relation to Simulated Annealing, with significantly better solutions, in an equal computation time. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Meta-heuristics are some of the best-known techniques to approach hard optimization problems, however, there are still questions about what makes some meta-heuristics better than others in a specific problem. This paper presents an analysis of the Firefly and Cuckoo Search Algorithm, such as others meta-heuristics. In order to assess the performance of the Firefly Algorithm and the Cuckoo Search Algorithm, they were compared with other well-known optimization techniques, such as Simulated Annealing and Local Search. Both meta-heuristics analysed in an in-depth computational study, reaching the conclusion that both techniques could be useful in Scheduling Problems and lead to satisfactory solutions quickly and efficiently. Moreover, the results of the analysis show that the Firefly Algorithm, despite having a high runtime, performs better than the other techniques. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.