A KNOWLEDGE BASED APPROACH TO PRODUCTION PLANNING AND SCHEDULING IN A METALLURGICAL COMPANY

Decision-making supported by task-oriented software tools plays more and more role in the production companies, including metallurgical plants. Decision-making in production planning and scheduling requires the response in an interactive real-time mode. It is an incentive for developing decision support system (DSS) that enables a fast prototyping of production flows in multi-project environment. The paper aims at providing a knowledge base approach allowing one to be independent of context or representation data as well as allowing for the design of an interactive and task-oriented DSS. The assumed knowledge base mode of specifying a production system leads to solving a decision problem formulated in terms of constraint satisfaction problem (CSP). Possible scenarios of the CSP decomposition as well as possibility of different programming languages application lead to a problem of searching for a distribution strategy that enables a real-time mode. A declarative form of the description of a multicriteria decision problem allows its implementation in constraint programming languages and facilitates the development of DSS. Illustrative example concerns optimal steelmaking process scheduling with constraints such as processing time, limited waiting time between adjacent tasks, and amount of resources allocated to tasks. Numerical experiments present the use of constraint programming approach, including various search strategies, to production planning and scheduling in the context of a metallurgical company.