Optimization and Engineering is a multidisciplinary
journal. Its primary goal is to promote the application of
optimization methods in the general area of engineering sciences.
This includes facilitating the development of advanced optimization
methods for direct or indirect use in engineering sciences.
The journal provides a forum in which
engineering scientists obtain information about recent
advances of optimization sciences, and researchers in mathematical
optimization learn about the needs of engineering sciences
and successful applications of optimization methods.
Its aim is to close the gap between optimization theory and
the practice of engineering.
All optimization methods of relevance to applications in
engineering sciences will be considered: deterministic and
stochastic, continuous, mixed integer and discrete, when they are
relevant for applications in engineering sciences. The journal
also strives to publish successful applications of optimization in
various engineering areas.
The scope of the journal includes the following:
- OPTIMIZATION:
All mathematical methods and algorithms
of mathematical optimization. Numerical and implementation
issues, optimization software, bench-marking, case studies.
Specifically:
linear and convex optimization, general nonlinear and
nonlinear mixed-integer optimization, combinatorial
optimization, equilibrium, multilevel and
multi-objective optimization, stochastic optimization.
- ENGINEERING:
Electrical engineering, VLSI design, robotics,
mechanical and structural engineering, multidisciplinary
design optimization (MDO),
geophysical engineering, civil engineering, industrial
engineering, chemical and process engineering,
aerospace engineering, water management,
environmental and bio-engineering, transportation and
communication sciences.
- EDUCATION:
The goal of the education section is to promote understanding and
appreciation of optimization theory and techniques. The Education
section will publish material aimed at educating students, engineers,
managers, and potential users of optimization methodology. All
submitted articles should be written at a level appropriate for
readers without a strong background in optimization.
