OPAL: A multi-knowledge-based system for industrial job-shop scheduling†

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Abstract
A job-shop scheduling software currently under development is described, based on artificial intelligence programming techniques. The idea is 10 be able to make three kinds of knowledge cooperate in the derivation of a feasible schedule: theoretical knowledge (issued form scheduling theory) which achieves the management of time; empirical knowledge about priority rules and their influence on production objectives: and practical knowledge (provided by shop-floor managers) about technological constraints to be satisfied in a given application. The latter is usually not considered in pure operations research algorithms. The system is actually implemented in COMMON LISP and runs on a Texas Explorer LISP Machine and a SUN workstation. Computational results are reported.