Aims & Scopes

Fixed Point Methods and Optimization (FPMO) is a peer-reviewed international journal dedicated to the development, analysis, and application of fixed-point methodologies, especially in optimization. The journal provides a rigorous platform for the dissemination of original research, computational techniques, and applied studies centered on fixed-point approaches.

FPMO emphasizes both theoretical advancements and practical implementations, particularly in the design, analysis, and application of fixed-point algorithms for complex optimization models arising in diverse scientific and engineering domains.

Focused Areas

• Fixed-Point Methods in Optimization
  The journal invites contributions on the formulation and analysis of fixed-point methods for solving optimization problems, including iterative schemes, projection methods, and operator-based approaches.
• Convex and Non-Convex Optimization
  Research addressing fixed-point techniques for convex and non-convex optimization problems, including nonlinear optimization frameworks and large-scale optimization models.
• Variational Inequalities and Equilibrium Problems
  Contributions on fixed-point formulations and solution methods for variational inequalities, complementarity problems, and equilibrium models.
• Stochastic and Multi-Objective Optimization
  Studies involving fixed-point approaches in stochastic optimization, uncertainty modeling, and multi-objective optimization problems.
• Algorithmic Development and Convergence Analysis
  Research focusing on the design, convergence analysis, and computational efficiency of fixed-point algorithms for optimization.
• Data-Driven and Computational Methods
  The journal encourages work on data-driven optimization, optimization-based data mining, and integration of fixed-point methods with modern computational and learning frameworks.
• Applications of Fixed-Point Optimization Methods
  Applications in science, engineering, management, and related fields, supported by numerical experiments and real-world problem implementations.

Publication Types

• Original Research Articles presenting significant theoretical or applied contributions
• Review Articles offering comprehensive surveys of fixed-point methods and optimization
• Short Communications highlighting concise and impactful findings

Audience

FPMO targets researchers, mathematicians, engineers, and practitioners working in optimization theory, nonlinear analysis, and computational methods, particularly those interested in fixed-point techniques and their applications.