Fuzzy set theory provides an intuitive and computationally simple way of dealing with uncertain and ambiguous properties. Decisions represented in terms of fuzzy sets are also flexible in their implementations. On the other hand, nonlinear programming relaxes the strict assumptions and constraints in linear programming and is more practicable. Many decision-making problems can also be represented in the form of nonlinear programming models. After combining these two issues, the resulting fuzzy nonlinear programming problem involving fuzzy parameters would be viewed as a more practicable version than the conventional one.

In the light of advanced computing systems, fuzzy nonlinear programming approaches become one of the most promising in practical applications. This special issue provides a forum for researchers and practitioners to review and disseminate quality research work on advanced fuzzy nonlinear programming approaches and their applications in the context of practicable and flexible decision making and to identify critical issues for further developments. Potential topics include, but are not limited to:

• Fuzzy nonlinear programming models
• Fuzzy fractional programming models
• Fuzzy polynomial programming models
• Type 2 fuzzy nonlinear programming models
• Interval-valued fuzzy nonlinear programming models
• Intuitionistic fuzzy nonlinear programming models
• Fuzzy semi-infinite programming models
• Random fuzzy nonlinear programming models
• Interactive fuzzy nonlinear programming approaches
• Fuzzy neural network (as a special case of fuzzy nonlinear programming)
• Fuzzy satisficing method
• New algorithm, heuristics, and metaheuristics
• Hybrid approaches and evolutional techniques
• Necessary conditions and constraint qualifications
• Duality and relaxation
• Nonlinear or linear programming equivalents
• Applications to practicable and flexible decision making

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