Decision Support Systems (DSS) are gaining increased popularity in various domains, including business, engineering, the military, and medicine. They are especially valuable in situations where the amount of available information is prohibitive for the intuition of an unaided human decision-maker and in which precision and optimality are of importance. Decision support systems can aid human cognitive deficiencies by integrating various sources of information, providing intelligent access to relevant knowledge, and structuring decisions. They can also support choice among well-defined alternatives and build on formal approaches, such as the methods of engineering economics, operations research, statistics, and decision theory. They can also employ artificial intelligence methods to address heuristic problems that are intractable by formal techniques. Proper application of decision-making tools increases productivity, efficiency, and effectiveness and gives many businesses a comparative advantage over their competitors, allowing them to make optimal choices for technological processes and their parameters, planning business operations, logistics, or investments.
These systems allow individuals and organizations to deal with unstructured or semi-structured decision problems that demand extensive experience and expert knowledge. However, the increasing complexity of the problems and the continuous growth of information and knowledge that responsible people in organizations should master underline the need for DSSs driven by advanced and modern technologies. From this perspective, the field of DSS is expanding to use new technologies such as Social Media, Semantic Web, Linked Data, Big Data, and Machine Learning. These technologies are converging to provide integrated support for individuals and organizations to make more rational decisions
The Seventh International Workshop on Intelligent Decision Support Systems for Industry Application (WIDSSI 2021), colocated with the 20th Mexican International Conference on Artificial Intelligence (MICAI 2021), will be aimed to bring together researchers, developers, and practitioners involved in the research area of Industrial Engineering, Computer Science, Management Science, Systems Engineering, Operations Research, Optimization Process, Software Engineering, Computational Engineering, Innovation Systems, Logistics Engineering, among others.
This Workshop aims to investigate and disseminate trends among innovative and high-quality research regarding the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms, and models for developing Intelligent Decision Support Systems for Industry
This track will offer the opportunity to present recent results and about Intelligence Decision Support System, Knowledge-based System for Optimization Process, theory, methods, systems, and its applications in any industry.
The principal objective of this track will be to know trends and new models’ development for researchers and practitioners in the area of Intelligence Decision Support System, Knowledgebased System for Optimization Process, to report the main applications and facilitate the growth in this field research.
The list of topics includes, but is not limited to:
Expert Systems for Optimization Process
Application of Knowledge-Based Methods
Software Tools for Knowledge-Based Systems Construction
Knowledge Acquisition & Representation
Knowledge-Based Implementation Techniques and System Architectures
Artificial Intelligence and DSS
Artificial Intelligence and BlockChain Technology in Logistics and
Supply Chain Management
Business Intelligence for Optimization Process
Collaborative Decision Making for Optimization Process
Internet of Things (IoT) in Logistics and Supply Chain Management
DSS Foundations and Development
Operational Research and Management Science
Modeling Techniques of Decision Support Systems
Industrial and Engineering Applications of Decision Support Systems
Decision Support Systems for Optimization Process
Soft Computing Techniques for Optimization Process
Project Management Techniques and Operational Research
Knowledge-Based Decision Support Systems
Strategic Decision Support Systems in Supply Chain
Impact of DSS in Industrial Performance
Artificial Intelligence Applying In Supply Chain
Machine Learning-based Applications
Neural Networks and Deep Learning Applications
Sentiment Analysis and Opinion Mining in social media
Natural Language Processing Techniques
Simulation in Logistics and Supply Chain
The economic impact of DSS in industry
Human Factors in DSS Development
Reliability in DSS
As in previous years, accepted papers will be included in the proceedings, which will be published in a special issue of the journal Research in Computer Science, ISSN 1870-4069.
The best papers will be selected to be published as an extended version of the book published by Springer-Verlag.
Due to the outbreak of COVID-19 and our participants' safety, WIDSSI will be held online (a virtual conference without any physical participation).
Interested parties are invited to submit a technical paper written in English in LNCS Springer style, not exceeding eight pages. The details of the format can be found at Lecture Notes in Computer Science: Information for LNCS Authors. The submissions must not contain authors' names or affiliations. They must not include either any information that may reveal the authors' identities. All submissions must not have been previously published or be under consideration for publication elsewhere. Submissions failing to meet these requirements will be rejected without revision.
All submitted papers will undergo a rigorous peer-review process that will consider programmatic relevance, scientific quality, significance, originality, style, and clarity.
In order to submit a paper electronically, authors must send an email with the subject: "WIDSSI20 Submission" to Cuauhtémoc Sanchez-Ramirez, Giner Alor-Hernandez, and Jorge Luis Garcia-Alcaraz (see below for corresponding email addresses) with the paper attached in PDF format and the body of the message should contain the following data:
1. Paper title.
2. Authors' names and affiliations.
3. Postal address, e-mail address and phone number of the contact authors.
4. The abstract of the paper.
5. Up to five keywords.
Please contact any of the workshop organizers in case you have any doubt or problem with electronic submissions.