An introduction to structured modeling
Management Science
A modeling language for mathematical programming
Management Science
The SML language for structured modeling: levels 1 and 2
Operations Research
Meta-modeling concepts and tools for model management: a systems approach
Management Science
BLOOMS: a prototype modeling language with object oriented features
Decision Support Systems
Type and inheritance theory for model management
Decision Support Systems
Integrating AI and optimization for decision support: a survey
Decision Support Systems - Special double issue: unified programming
Database structures for mathematical programming models
Decision Support Systems
Constraint logic programming framework for integrated decision supports
Decision Support Systems
The Unified Modeling Language user guide
The Unified Modeling Language user guide
Future trends in model management systems: parallel and distributed extensions
Decision Support Systems
Decision Support Systems
Inheritance rules for flexible model retrieval
Decision Support Systems
Designing OQL: allowing objects to be queried
Information Systems
Model and data integration and re-use in environmental decision support systems
Decision Support Systems
The object data standard: ODMG 3.0
The object data standard: ODMG 3.0
Designing personalized intelligent financial decision support systems
Decision Support Systems
Using soft computing to build real world intelligent decision support systems in uncertain domains
Decision Support Systems - Special issue on decision support in the new millennium
The state of the art in agent communication languages
Knowledge and Information Systems
Past, present, and future of decision support technology
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
A new paradigm for computer-based decision support
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Distributing decision support systems on the WWW: the verification of a DSS metadata model
Decision Support Systems
Integrated Modeling Environments in Organizations: An Empirical Study
Information Systems Research
Generating optimization-based decision support systems
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Model Management in Electronic Markets for Decision Technologies: A Software Agent Approach
HICSS '97 Proceedings of the 30th Hawaii International Conference on System Sciences: Advanced Technology Track - Volume 5
A real-time synchronization mechanism for collaborative model management
Decision Support Systems
A framework for developing optimization-based decision support systems
Expert Systems with Applications: An International Journal
Flexible modelling and support of interrelated decisions
Decision Support Systems
Enterprise model management systems
Proceedings of the International Workshop on Enterprises & Organizational Modeling and Simulation
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Complex mathematical models are being increasingly adopted for corporate decision-making, and lay users are becoming more involved through institutional decision-making processes. Because of the technical complexity and variability of mathematical models, difficulties arise in supporting complicated model solution processes and in maintaining new models with existing solvers (i.e., problem-solving algorithms). This paper proposes an intelligent model-solver integration framework that facilitates an intuitive and user-friendly model solution process and evolutionary model maintenance. Specifically, for an intuitive model solution, the framework gives a model management system the ability to suggest autonomously compatible solvers of a model without direct user intervention. In addition, it solves the model by matching intelligently model parameters with solver parameters without any serious conflicts. Thus, the framework improves the productivity of institutional model solving tasks by relieving the user from the risk of erroneous application of a solver to syntactically and semantically incompatible models, and by reducing the burden given by the considerable learning process of model and solver semantics.