Journal Description
Title: Journal of Computational Analytics and Decision Optimization
ISSN: Applied
Journal Abbreviation: J. Comput. Anal. Decis. Optim.
Publication language: English
Publishing frequency: Quarterly (March, June, September, December)
Download Article Template click here
DOI Prefix: 10.54392/jmipe
ISSN: Applied
Journal Abbreviation: J. Comput. Anal. Decis. Optim.
Publication language: English
Publishing frequency: Quarterly (March, June, September, December)
Download Article Template click here
DOI Prefix: 10.54392/jmipe
Aim and Scope
The Journal of Computational Analytics and Decision Optimization (JCADO) is an international, peer-reviewed scholarly journal dedicated to the advancement of computational methods, analytical models, and optimization approaches for complex decision-making problems across science, engineering, technology, industry, and interdisciplinary applications.
The journal provides a focused platform for high-quality theoretical, methodological, computational, and application-oriented research that integrates computational analytics with decision modelling and optimization. JCADO particularly encourages research in which data, algorithms, mathematical models, computational intelligence, and optimization techniques are systematically combined to improve prediction, decision-making, resource allocation, system performance, and operational efficiency.
The primary aim of JCADO is to promote innovative research that advances the development, analysis, validation, and practical application of computational and optimization methodologies. The journal welcomes fundamental methodological contributions as well as rigorously validated applications that demonstrate measurable improvements over established approaches.
JCADO seeks contributions that demonstrate methodological originality, analytical rigor, reproducibility, appropriate validation, and clear scientific or practical significance. Studies applying established computational methods to new datasets or application domains should demonstrate substantial analytical insight, methodological adaptation, comparative evaluation, or decision-making value beyond routine implementation.
The journal provides a focused platform for high-quality theoretical, methodological, computational, and application-oriented research that integrates computational analytics with decision modelling and optimization. JCADO particularly encourages research in which data, algorithms, mathematical models, computational intelligence, and optimization techniques are systematically combined to improve prediction, decision-making, resource allocation, system performance, and operational efficiency.
The primary aim of JCADO is to promote innovative research that advances the development, analysis, validation, and practical application of computational and optimization methodologies. The journal welcomes fundamental methodological contributions as well as rigorously validated applications that demonstrate measurable improvements over established approaches.
JCADO seeks contributions that demonstrate methodological originality, analytical rigor, reproducibility, appropriate validation, and clear scientific or practical significance. Studies applying established computational methods to new datasets or application domains should demonstrate substantial analytical insight, methodological adaptation, comparative evaluation, or decision-making value beyond routine implementation.
