Optimization Theory and Applications in Engineering, Management and Other Fields
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".
Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 2420
Special Issue Editors
Interests: applied mathematics; computational optimization
Special Issue Information
Dear Colleagues,
Optimization has a far-reaching use and applications in different disciplines. It has been used in engineering, management, policy design, and so on. Due to its applicability and the introduction of new and challenging problems, the study of optimization methods has been one of the focus points in applied disciplines. Depending on the nature of the problem, it can be classified in different ways. Multi-objective versus single objective is one classification, where the former deals with simultaneous optimization of, often conflicting, multiple objectives. Dynamic versus static is another classification where dynamic is when a time-dependent model is under consideration. Deterministic versus non-deterministic is another classification based on the level of information on the quantities under consideration. Non-deterministic considers when there is incomplete information where these quantities can be stochastic, fuzzy, or grey. Solution methods for these problems can be classical or heuristic based. With the development of computational tools, heuristic algorithms are popular for challenging optimization problems including black box optimization.
This Special Issue is devoted to the advances in this area. Hence, possible focus topics include, but are not limited to:
- Linear and non-linear programming
- Stochastic optimization
- Fuzzy optimization
- Grey optimization
- Multi objective optimization
- Multilevel optimization
- Optimal control
- Dynamic optimization
- Metaheuristics
- Hyperheuristics
- Matheuristics
Dr. Surafel Luleseged Tilahun
Prof. Dr. F. Mora-Camino
Guest Editors
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Keywords
- linear and non-linear programming
- stochastic optimization
- fuzzy optimization
- grey optimization
- multi objective optimization
- multilevel optimization
- optimal control
- dynamic optimization
- metaheuristics
- hyperheuristics
- matheuristic
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