A pattern matching method for large-scale multipurpose process scheduling

Abstract

This article proposes a novel pattern matching method for the large-scale multipurpose process scheduling with variable or constant processing times. For the commonly used mathematical programming models, large-scale scheduling with long-time horizons implies a large number of binary variables and time sequence constraints, which makes the models intractable. Hence, decomposition and cyclic scheduling are often applied to such scheduling. In this work, a long-time horizon of scheduling is divided into two phases. Phase one is duplicated from a pattern schedule constructed according to the principle that crucial units work continuously, in parallel and/or with full load as possible, exclusive of time-consuming optimization. Phase two involves a small-size subproblem that can be optimized easily by a heuristic method. The computational effort of the proposed method does not increase with the problem size. The pattern schedule can be not only used for production/profit maximization but also for makespan estimation and minimization. Copyright © 2010 American Institute of Chemical Engineers (AIChE).