JOURNAL OF CONVEX ANALYSIS

Scope & Guideline

Fostering Interdisciplinary Collaboration in Mathematics.

Introduction

Immerse yourself in the scholarly insights of JOURNAL OF CONVEX ANALYSIS with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN0944-6532
PublisherHELDERMANN VERLAG
Support Open AccessNo
CountryGermany
TypeJournal
Convergefrom 1996 to 1999, from 2001 to 2024
AbbreviationJ CONVEX ANAL / J. Convex Anal.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressLANGER GRABEN 17, 32657 LEMGO, GERMANY

Aims and Scopes

The Journal of Convex Analysis focuses on advancing the field of convex analysis, emphasizing both theoretical and applied aspects. It serves as a platform for researchers to explore the rich interplay between convexity, optimization, and functional analysis.
  1. Convex Functions and Sets:
    The journal publishes research on the properties, characterizations, and applications of convex functions and sets, exploring their role in optimization and analysis.
  2. Optimization Problems:
    A significant focus is on various optimization problems, including convex and non-convex scenarios, duality theories, and computational approaches.
  3. Variational Analysis:
    Papers often delve into variational analysis, studying the relationships between convex functions and variational principles, including existence and uniqueness results.
  4. Functional Analysis:
    Research that connects convex analysis with functional analysis is central, particularly in the study of Banach and Hilbert spaces, and their applications in optimization.
  5. Applications in Economics and Game Theory:
    The journal also explores applications of convex analysis in economics, including equilibrium problems and optimal control in economic models.
  6. Stochastic Processes and Optimization:
    Recent papers indicate a growing interest in the intersection of stochastic processes and convex optimization, focusing on applications in dynamic systems and decision-making.
The Journal of Convex Analysis has been witnessing exciting trends and emerging themes, reflecting the evolving landscape of the field. Recent publications reveal areas of growing interest and innovative research directions.
  1. Stochastic Optimization and Control:
    There is an increasing focus on stochastic optimization and control problems, particularly those that integrate convex analysis with stochastic processes and dynamic systems.
  2. Applications of Convex Analysis in Machine Learning:
    Research that applies convex analysis principles to machine learning, particularly in optimization algorithms and model training, is gaining traction, highlighting the relevance of convexity in contemporary computational methods.
  3. Variational Methods in PDEs:
    Emerging themes include variational methods applied to partial differential equations (PDEs), indicating a trend towards using convex analysis techniques to address complex problems in mathematical physics and engineering.
  4. Multi-Objective Optimization:
    An uptick in research on multi-objective optimization problems showcases a burgeoning interest in trade-offs and optimal solutions in settings with multiple competing objectives.
  5. Geometric Aspects of Convexity:
    There is a growing trend towards exploring the geometric aspects of convexity, particularly in relation to convex bodies and their properties, underscoring the interplay between geometry and analysis.

Declining or Waning

While the journal continues to thrive in many areas, some themes appear to be diminishing in frequency or importance. These trends indicate shifts in research focus within the community.
  1. Classical Convex Analysis:
    Papers that purely focus on classical aspects of convex analysis, such as basic properties of convex sets and functions, seem to be less frequent, indicating a possible shift towards more complex applications and interdisciplinary approaches.
  2. Nonlinear Programming without Convexity:
    There has been a noticeable decline in publications addressing nonlinear programming problems that do not incorporate convexity, suggesting a preference for convex frameworks in recent research.
  3. Static Optimization Problems:
    Research centered on static optimization problems—those that do not incorporate dynamic or time-varying elements—appears to be waning, as the field increasingly embraces dynamic and stochastic models.

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