Open AccessMulti-periodic Refinery Scheduling Based on Generalized Disjunctive Programming
Author(s) -
Ming Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1575/1/012195
Subject(s) - refinery , scheduling (production processes) , computer science , mathematical optimization , dynamic priority scheduling , heuristic , job shop scheduling , mathematics , artificial intelligence , engineering , schedule , operating system , waste management
Refinery complex production process usually involves some distinct or implied production rules and expert experiences. Representation and utilizing these heuristic rules is conducive to efficient scheduling optimization. In this paper, the heuristic rules were formulated using disjunctive form and logical proposition, and a discrete-time based multi-periodic generalized disjunctive programming (GDP) scheduling model was built. Due to the combining of logic expressions and algebra expressions, heuristic rules were utilized by the proposed model, while scheduling optimization was ensured. The formulated model was used to deal with a refinery scheduling problem. Case study shows the model’s feasibility and efficiency.