An emerging, yet extremely important topic in simulation application and research is simulation optimization. Emphasis in the literature, in professional conferences, and particularly in commercial software packages underscore the importance of simulation optimization. We address this topic in a more general, model optimization venue. In particular we describe the use of a genetic algorithm in ...

Forecasting the behavior of variables (e.g., economic, financial, physical) is of strategic value for organizations, which helps to sustain practical interest in the development of alternative models and resolution procedures. This paper presents a non-linear model that combines radial basis functions and the ARMA(p,q) structure. The optimal set of parameters for such a model is difficult to fi...

In this paper the problem of designing optimal logical topologies for WDM networks using the tabu search meta-heuristic has been considered. For a given physical topology and requests for data communication at specified rates between different pairs of nodes in the network, our objective is to obtain a logical topology, using the tabu search, to minimize the network congestion.

The ability of some RNA molecules to switch between different metastable conformations plays an important role in cellular processes. In order to identify such molecules and to predict their conformational changes one has to investigate the refolding pathways. As a qualitative measure of these transitions, the barrier height marks the energy peak along such refolding paths. We introduce a meta-...

Different kinds of meta-heuristic algorithms have been recently utilized to overcome the complex nature of optimum design of structures. In this paper, an integrated optimization procedure with the objective of minimizing the self-weight of real size structures is simply performed interfacing SAP2000 and MATLAB® softwares in the form of parallel computing. The meta-heuristic algorithm chosen he...

The gap in automation between MIP/SAT solvers and those for constraint programming and constraint-based local search hinders experimentation and adoption of these technologies and slows down scientific progress. This paper addresses this important issue: It shows how effective local search procedures can be automatically synthesized from models expressed in a rich constraint language. The synth...

Radial Basis Function Neural Networks (RBF NNs) are one of the most applicable NNs in the classification of real targets. Despite the use of recursive methods and gradient descent for training RBF NNs, classification improper accuracy, failing to local minimum and low-convergence speed are defects of this type of network. In order to overcome these defects, heuristic and meta-heuristic algorith...

Hyper-heuristics can be thought of as heuristic management methodologies which are motivated by the goal of building a high level of generality in the scope of computational search methodologies [2] [7]. Most meta-heuristics (and other search methods) perform a search over the solution space directly, whereas, hyper-heuristics as high level strategies search a heuristic space. One of the hyper-...