Clustering search

This paper presents the Clustering Search (CS) as a new hybrid metaheuristic, which works in conjunction with other metaheuristics, managing the implementation of local search algorithms for optimization problems. Usually the local search is costly and should be used only in promising regions of the search space. The CS assists in the discovery of these regions by dividing the search space into clusters. The CS and its applications are reviewed and a case study for a problem of capacitated clustering is presented.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal do MaranhãoUniversidade Federal de São Paulo (UNIFESP)Instituto Nacional de Pesquisas EspaciaisUNIFESPSciEL

Simplified methods for the minimization of open stacks problem.

Este trabalho apresenta dois m?todos para a solu??o do Problema de Minimiza??o de Pilhas Abertas (ou MOSP, de Minimization of Open Stacks Problem), um problema de sequenciamento de padr?es oriundo do contexto de produ??o de pe?as, cuja aplica??o industrial ? direta. O primeiro ? relativo a uma heur?stica baseada em teoria de grafos e crit?rios gulosos, enquanto o segundo ? relativo a um m?todo de programa??o din?mica. Os resultados do experimento realizado comprovam a efic?cia das simplifica??es propostas quando comparadas com os m?todos da literatura.This paper presents two methods for solving the minimization of open stack problem (MOSP), a pattern sequencing problem found in production systems with direct industrial application. The first method refers to a heuristic based on graph theory and greedy criteria, while the second refers to the dynamic programming method. The results show the effectiveness of the proposed simplifications compared to the methods reported in the literature