Classical optimization and, more recently, hybrid optimization have been successfully applied to many aspects of engineering and economics. For example, as reported in the literature, gravitational search algorithm, genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), and several hybrid swarm evolutionary algorithms have been adopted to handle complex and uncertain real world optimization problems. On the other hand, advances in hybrid optimization techniques are an important section in engineering and economics and also assist optimization algorithm experts to develop better methods. In order to bridge the concepts and methodologies from the two ends, this special issue concentrates on the related topics of integrating and utilizing algorithms in hybrid computational intelligent techniques and their applications in engineering and economics. The hybrid systems can be a hybrid among the classical methods between the classical methods and artificial intelligence based methods or among the artificial intelligence based methods. It provides the opportunity for practitioners to hand their complicated real world issues by using hybrid optimization methodologies and for researchers to realize the significant contribution to the body of the knowledge and look into future directions.

This special issue aims at providing a forum for adopting the state-of-the-art hybrid optimization techniques in engineering and economics, developing the advanced hybrid optimization techniques by using meta-heuristics approaches, exchanging of related ideas, and discussing the future directions. A special attention will be paid to the exchange between comparison and combination of the classical, more mathematical, and model-based methods of optimization and the many emerging model-free methods from computer science. Herewith, we aim to strengthen the mathematical and engineering sciences and to contribute to industries, economies, and living conditions on earth. We invite researchers to submit their original and unpublished work.

Potential topics include, but are not limited to:

• Classical optimization methods of mathematics and their applications in engineering and economics
• Continuous optimization applications in engineering and economics
• Combinatorial optimization applications in engineering and economics
• Mixed-integer programming applications in engineering and economics
• Hybrid optimization with metaheuristics techniques Multiobjective hybrid optimization approachesHandling uncertainties with hybrid optimization
• Langrage optimization
• Kuhn-Tucker optimization
• Chaotic hybrid optimization
• Linear and nonlinear optimization
• Mathematical programming
• Theoretical aspects of hybrid optimization methods Emerging real world and theoretical applications in engineering and economics