In the recent past, metaheuristics have been developed to solve a wide range of optimization problems in various fields of engineering and science. Some representative examples, such as genetic algorithms, particle swarm optimization, and artificial bee colony, are used to solve many hard optimization problems effectively and establish powerful search capabilities for solving such problems. In spite of these advantages, these metaheuristics still encounter challenges when solving real-world and large scale optimization problems, forcing the development of new solution procedures whose efficiency is measured by their ability to find acceptable solutions within a reasonable computational expense.

Hybrid intelligence is recognized as an integration of different metaheuristic approaches and thoughts to overcome individual limitations and achieve synergistic effects. Such hybridizations can be used to take the advantage of strengths from different intelligent techniques and overcome the difficulties of the metaheuristics when applied to solve the problems individually.

The aim of this special issue is to archive the innovative advancements and mathematical modeling of hybrid intelligence for handling complex optimization problems, which may depend largely on methods from computational intelligence and operations research. This special issue is a forum for researchers to review and disseminate quality research on hybrid intelligent techniques with emphasis on mathematical modeling and analysis of algorithms with applications in the context of engineering and science. Potential topics include, but are not limited to:

• Mathematical modeling and evaluation of new hybrid intelligent techniques based on:
• modular integration of two or more metaheuristics, retaining the identity of each methodology
• fusion: transforming the knowledge representation in one methodology into another form of representation to another methodology

• Theoretical and technological advancements in mathematical methods for hybrid intelligent techniques, with validation through convincing computational experiments, comparison, and convergence proof
• Application of hybrid intelligent techniques for real-world and large scale optimization problems (all fields of engineering and science)

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/mpe/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/mpe/hitt/ according to the following timetable: