Developing model strings for model managers
Journal of Management Information Systems
An intelligent system for formulating linear programs
Decision Support Systems
Model management systems: design for decision support
Decision Support Systems
A database language for sets, lists and tables
Information Systems
Extending a database system with procedures
ACM Transactions on Database Systems (TODS)
SQL/NF: a query language for ¬ 1NF relational databases
Information Systems
ACM Transactions on Database Systems (TODS)
An introduction to structured modeling
Management Science
Introduction to SQL
Algorithmic graph theory
Query processing techniques in the summary-table-by-example database query language
ACM Transactions on Database Systems (TODS)
An introduction to database systems: vol. 1 (5th ed.)
An introduction to database systems: vol. 1 (5th ed.)
The relational model for database management: version 2
The relational model for database management: version 2
A modeling language for mathematical programming
Management Science
Derived relations with exceptions: decision support capabilities
Journal of Management Information Systems
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
FW/SM: a prototype structured modeling environment
Management Science
An interior point algorithm to solve computationally difficult set covering problems
Mathematical Programming: Series A and B - Special issue on interior point methods for linear programming: theory and practice
Performance analysis of “what-if” databases using independently updated views
Journal of Management Information Systems
Databsse system approach the management decision support
ACM Transactions on Database Systems (TODS)
Set Covering by an All Integer Algorithm: Computational Experience
Journal of the ACM (JACM)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Extensions to Query Languages for Graph Traversal Problems
IEEE Transactions on Knowledge and Data Engineering
Extending SQL with General Transitive Closure and Extreme Value Selections
IEEE Transactions on Knowledge and Data Engineering
Non First Normal Form Relations and Recursive Queries: An SQL-Based Approach
Proceedings of the Third International Conference on Data Engineering
Designing A Generalized NF2 Model with an SQL-Type Language Interface
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
A critique of the SQL database language
ACM SIGMOD Record
Graph Theory With Applications
Graph Theory With Applications
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Graph matching, set covering, and partitioning problems are both theoretically and practically important in decision support systems. Numerous decision support applications have been modeled as graph matching, set covering, and partitioning problems. These include applications in the areas of task assignment, marriage problem, airline crew scheduling, truck deliveries or vehicle routing, political redistricting, and the like. Currently, these applications are supported through programs written in external (to the database system) programming languages that use only the data in the database system. Thus, decision makers or application programmers require extra effort to get required decision support information. As opposed to database systems, the purpose of a model management system (MMS) is to make a wide variety of models available to decision makers so they can apply these models without having to become involved in technical and/or procedural aspects of implementation. The goal of this research is to integrate database systems and model systems for zero-one integer programming problems especially concerning graph matching, set covering, and partitioning problems. Users utilize a single integrated language for both problem formulation and model execution. In order to achieve this goal, we extend relational operators and the query language SQL. The relational operators are extended with six operators, namely, match, maxmatch, cover, mincover, partition, and minpartition. Some of these operators may take a very long time to find an optimal solution. In this article, we adopted genetic algorithms to find a near-optimal solution of this kind of operators. We found they performed well both on the computational effort and on the quality of the solutions through a variety of test problems. These algorithms are bounded by a polynomial time. Therefore, they enable a DBMS to respond to queries involving proposed operators in a restricted amount of time.