Aims and scope

Annals of Optimization With Applications (ANOWA) is a distinguished, international peer-reviewed journal focused on advancing optimization methodologies in science, engineering, and beyond. As an open-access publication, ANOWA ensures that all articles are freely available to a global audience, fostering an environment where knowledge and innovation can be shared without barriers. The journal encourages interdisciplinary exploration and collaboration, targeting both theoretical and practical advancements in optimization across a wide range of domains.

Aims and Scope: The Annals of Optimization With Applications (ANOWA) is dedicated to providing a comprehensive platform for the dissemination of both theoretical and practical advancements in the field of optimization. The journal's aims and scope encompass a wide spectrum of topics, including but not limited to:

  1. Optimization Theory: Contributions to foundational optimization theory, covering linear, nonlinear, convex, and nonconvex optimization, as well as advances in mathematical programming.

  2. Algorithm Development: Development of novel algorithms for optimization problems, including gradient-based, derivative-free, metaheuristic, and evolutionary algorithms, addressing both unconstrained and constrained challenges.

  3. Computational Studies: Papers that focus on computational aspects of optimization, including complexity analysis, numerical methods, parallel and distributed computing, and software development for optimization.

  4. Large-Scale and Complex Systems: Research on optimization techniques applicable to large-scale systems, network optimization, and combinatorial optimization, with applications in engineering, logistics, telecommunications, and infrastructure.

  5. Stochastic and Robust Optimization: Studies addressing optimization under uncertainty, including stochastic programming, robust optimization, and chance-constrained models, applicable to dynamic and unpredictable environments.

  6. Multi-Objective and Goal Programming: Contributions that explore optimization involving multiple objectives, including Pareto optimization, goal programming, and trade-off analysis, with applications in economics, engineering, and sustainability.

  7. Quantum and Emerging Optimization Techniques: Exploration of quantum optimization methods, machine learning-assisted optimization, and other emerging technologies that push the boundaries of conventional approaches.

  8. Data-Driven Optimization: Approaches that incorporate data analysis and machine learning into optimization problems, including data envelopment analysis, big data optimization, and predictive modeling for decision support.

  9. Applications of Optimization: Practical applications of optimization methodologies in various domains such as transportation, energy, healthcare, manufacturing, finance, supply chain management, and smart cities, demonstrating the real-world impact of optimization research.

  10. Interdisciplinary Research: Emphasis on interdisciplinary contributions that integrate optimization with other fields, including artificial intelligence, computer science, operations research, economics, and the social sciences, promoting collaboration across disciplines.

  11. Review and Survey Articles: In addition to original research, ANOWA welcomes high-quality review and survey articles that summarize recent advancements, highlight emerging trends, and outline future directions for research in optimization.

Topics of Interest:

  • Large Scale Optimization

  • Uncertain Optimization

  • Stochastic algorithms in systems engineering

  • Unconstrained Optimization

  • Linear and Quadratic Programming

  • Convex Programming

  • Nonlinear Programming

  • Intelligent Engineering Systems under Uncertainty

  • Constrained Optimization

  • Nondifferentiable Optimization

  • Integer Programming

  • Combinatorial Optimization

  • Quantum Optimization

  • Approximations and Error Analysis

  • Data Envelopment Analysis

  • Stochastic Optimization

  • Multi-objective Optimization

  • Network Optimization

  • Parametric Programming and Sensitivity Analysis

  • Computational Optimization

  • Parallel Computing, Distributed Computing, and Vector Processing

  • Complementarity Problems

  • Software, Benchmarks, Numerical Experimentation and Comparisons

  • Modelling Languages and Systems for Optimization

  • Transportation, Manufacturing, and Management Science

The journal aims to foster a deeper understanding of optimization methodologies and their diverse applications, providing a rigorous academic forum where researchers, practitioners, and policymakers can contribute and access cutting-edge research. By offering a platform for the dissemination of innovative techniques and their applications, ANOWA seeks to play a pivotal role in shaping the future of optimization in a wide range of scientific and engineering