Even the biggest success Starts with a first step

Advances in operation research and computer sciences have provided, and will continue to provide, promising solutions to some long standing challenges in many industries.

Metaheuristics and Probabilistic Graphical Modeling Techniques are two newly emerged branches of optimization and computer science, that related to approximate algorithms. Probabilistic Graphical Modeling is a natural idea to deal with logistic problems in a large-scale complex system with a variety of uncertainties. Numerous techniques have been developed for the general graphical formalism of complex system in terms of its modularity and the probabilistic characteristics of individual parts. Metaheuristics represent those general approximate algorithms applicable to a large variety of complex problems that are believed to be hard to solve analytically or with simulation-based methods. To ultra-high dimension complex problem, faster and robust results can be achieved through exploring the possible solutions with superior computational searches, in a set of reduced possible spaces identified by the state-of-the-art algorithms. The marriage between the two then may provide solutions to some problems that are difficult with conventional methodologies.

Metaheuristics and Probabilistic Graphical Modeling Techniques have gained significant interests for their potentials in dealing with real-life problems in science, engineering, economics and business, especially the class of problems seen in a large-scale network or complex system. The past 20 years have witnessed the development of solutions to numerous problems in different research areas and industries.