The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often falls into these trap and therefore cannot converge to global optima solution. In this paper, an efficient hybrid optimization algorithm is developed for solving this problem, called Tabu-KM. It gathers the ...

ÐIn a fault-tolerant distributed system, it is often necessary for nonfaulty processes to agree on the value of a shared data item. The criterion of Approximate Agreement does not require processes to achieve exact agreement on a value; rather, they need only agree to within a predefined numerical tolerance. Approximate Agreement can be achieved through convergent voting algorithms. Previous re...

Hybrid models are mathematical models that comprise both mechanistic and black-box or datadriven components. Typically, the parameters in the mechanistic part of a hybrid model (if any) are assumed to be known. However in this research, a two-level approach is proposed for the identification of hybrid models where some parameters in the mechanistic part of the model are unknown. At the first le...

Multior many-objective evolutionary algorithms(MOEAs), especially the decomposition-based MOEAs have been widely concerned in recent years. The decomposition-based MOEAs emphasize convergence and diversity in a simple model and have made a great success in dealing with theoretical and practical multior many-objective optimization problems. In this paper, we focus on update strategies of the dec...

In this report, we study stochastic local search (SLS) algorithms for biobjective optimization problems. In particular, we study multi-objective algorithms that belong to two different classes of approaches, those that use a scalarized acceptance criterion (SAC) and those that use a componentwise acceptance criterion (CWAC). As a representative example of a SAC algorithm, we study Two-Phase Loc...