Welcome to the online submission and editorial system for Decision Science Letters


Decision Science Letters is a quarterly publication dedicated to create a forum for scientists in all over the world who wish to share their experience and knowledge in the field of Decision Sciences. The journal's policy is to perform a peer review on all submitted articles and the papers will be appeared in a form of online on our website as soon as the review result becomes positive. The journal covers both empirical and theoretical aspects of management and gives the chance on sharing knowledge among practitioners. We do our best to contribute to recent advances on multiple criteria decision making problems including the following

► Multi Criteria Decision Making   ► Grey Relational Analysis, COPRAS     ► Best-worst Method   ► MODM applications: NSGA-II, MOPSO   ► Fuzzy techniques: Fuzzy TOPSIS   ► Fuzzy DEMATEL, Fuzzy VIKOR   ► Parameter Tunning by MCDM techniques   ► Data mining and Data Clustering   ► MCDM techniques and Robust optimization   ► Engineering Optimization

► TOPSIS, VIKOR, AHP, ELECTERE, ...   ► Simulation optimization   ► Game theory   ► Supplier Selection and Green management   ► Reliability   ► Artificial Neural Network (ANN)   ► Non-traditional Machining Process   ► MCDM techniques in SCM   ► Data Envelopment Analysis   ► Travelling salesman problem (TSP), VRP, etc.

Decision Science Letters is an open access journal, which provides instant access to the full text of research papers without any need for a subscription to the journal where the papers are published. Therefore, anyone has the opportunity to copy, use, redistribute, transmit/display the work publicly and to distribute derivative works, in any sort of digital form for any responsible purpose, subject to appropriate attribution of authorship. Authors who publish their articles may also maintain the copyright of their articles.

Growing Science publishes peer reviewed high quality open access papers in various fields of sciences. The primary aim of this publishing company is to perform fast and reliable process for contributors. Once a paper is accepted, our staffs work hard to provide online version of the papers as quickly as possible. All papers are assigned valid DOI number once they appear online just to make sure that the other people researchers cite them while no volume and numbers are still assigned to the papers. We believe this could help the existing knowledge grow faster; however, the actual publication of a paper with volume and number will not exceed more than 4 months.  

Decision Science Letters applies the Creative Commons Attribution (CC BY) license to works we publish (read the human-readable summary or the full license legal code). Under this license, authors keep ownership of the copyright for their content, but permit anyone to download, reuse, reprint, modify, distribute and/or copy the content as long as the original authors and source are cited. No permission is needed from the authors or the publishers. Appropriate attribution can be provided by simply citing the original article (e.g., Rao, R. (2016). Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems. Decision Science Letters, 5(1), 1-30., 1-10. DOI: 10.5267/j.dsl.2015.9.003). For any reuse or redistribution of a work, users have to also make clear the license terms under which the work was published. This broad license was developed to facilitate free access to, and unrestricted reuse of, original works of all kinds. Applying this standard license to your own work will ensure that it is freely and openly available in perpetuity.

Most of the Growing Science published articles can be traced on Microsoft Academic search, Google Schoolar, Ulriches' web, Socolar, Genamics, Open J-Gate, Libraries of various well-known universities such as MIT, Washington State, GeorgeTown, Strathclyde, Tohoku, Indiana, North Dakota, York, Osaka, NovaNet, and Tamkang.

Decision Science Letters has been indexed by Web of Science, Scopus, DOAJ and Scimago.