Integrated planning, scheduling, and dynamic optimization for sequential batch processes

Yunfei Chu; Fengqi You

doi:10.1109/ACC.2015.7172222

Integrated planning, scheduling, and dynamic optimization for sequential batch processes

Yunfei Chu, Fengqi You

Chemical and Biological Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

We solve the challenging problem of integrated planning, scheduling, and dynamic optimization for sequential batch processes with fixed batch sizes. The integrated problem is first formulated into a complicated mixed-integer nonlinear programing (MINLP) problem. There are a planning model, multiple scheduling models in planning periods, and a number of dynamic models describing task execution processes. To efficiently solve the complex MINLP problem, we develop an efficient method which separates the subproblems using metamodels to represent the linking functions. Compared to the direct solution approach, the proposed method significantly reduces the computational time.

Original language	English (US)
Title of host publication	ACC 2015 - 2015 American Control Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5635-5640
Number of pages	6
ISBN (Electronic)	9781479986842
DOIs	https://doi.org/10.1109/ACC.2015.7172222
State	Published - Jul 28 2015
Event	2015 American Control Conference, ACC 2015 - Chicago, United States Duration: Jul 1 2015 → Jul 3 2015

Publication series

Name	Proceedings of the American Control Conference
Volume	2015-July
ISSN (Print)	0743-1619

Other

Other	2015 American Control Conference, ACC 2015
Country/Territory	United States
City	Chicago
Period	7/1/15 → 7/3/15

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/ACC.2015.7172222

Cite this

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title = "Integrated planning, scheduling, and dynamic optimization for sequential batch processes",

abstract = "We solve the challenging problem of integrated planning, scheduling, and dynamic optimization for sequential batch processes with fixed batch sizes. The integrated problem is first formulated into a complicated mixed-integer nonlinear programing (MINLP) problem. There are a planning model, multiple scheduling models in planning periods, and a number of dynamic models describing task execution processes. To efficiently solve the complex MINLP problem, we develop an efficient method which separates the subproblems using metamodels to represent the linking functions. Compared to the direct solution approach, the proposed method significantly reduces the computational time.",

author = "Yunfei Chu and Fengqi You",

note = "Publisher Copyright: {\textcopyright} 2015 American Automatic Control Council.; 2015 American Control Conference, ACC 2015 ; Conference date: 01-07-2015 Through 03-07-2015",

year = "2015",

month = jul,

day = "28",

doi = "10.1109/ACC.2015.7172222",

language = "English (US)",

series = "Proceedings of the American Control Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "ACC 2015 - 2015 American Control Conference",

address = "United States",

}

Chu, Y & You, F 2015, Integrated planning, scheduling, and dynamic optimization for sequential batch processes. in ACC 2015 - 2015 American Control Conference., 7172222, Proceedings of the American Control Conference, vol. 2015-July, Institute of Electrical and Electronics Engineers Inc., pp. 5635-5640, 2015 American Control Conference, ACC 2015, Chicago, United States, 7/1/15. https://doi.org/10.1109/ACC.2015.7172222

Integrated planning, scheduling, and dynamic optimization for sequential batch processes. / Chu, Yunfei; You, Fengqi.
ACC 2015 - 2015 American Control Conference. Institute of Electrical and Electronics Engineers Inc., 2015. p. 5635-5640 7172222 (Proceedings of the American Control Conference; Vol. 2015-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Integrated planning, scheduling, and dynamic optimization for sequential batch processes

AU - Chu, Yunfei

AU - You, Fengqi

PY - 2015/7/28

Y1 - 2015/7/28

N2 - We solve the challenging problem of integrated planning, scheduling, and dynamic optimization for sequential batch processes with fixed batch sizes. The integrated problem is first formulated into a complicated mixed-integer nonlinear programing (MINLP) problem. There are a planning model, multiple scheduling models in planning periods, and a number of dynamic models describing task execution processes. To efficiently solve the complex MINLP problem, we develop an efficient method which separates the subproblems using metamodels to represent the linking functions. Compared to the direct solution approach, the proposed method significantly reduces the computational time.

AB - We solve the challenging problem of integrated planning, scheduling, and dynamic optimization for sequential batch processes with fixed batch sizes. The integrated problem is first formulated into a complicated mixed-integer nonlinear programing (MINLP) problem. There are a planning model, multiple scheduling models in planning periods, and a number of dynamic models describing task execution processes. To efficiently solve the complex MINLP problem, we develop an efficient method which separates the subproblems using metamodels to represent the linking functions. Compared to the direct solution approach, the proposed method significantly reduces the computational time.

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U2 - 10.1109/ACC.2015.7172222

DO - 10.1109/ACC.2015.7172222

M3 - Conference contribution

AN - SCOPUS:84940935209

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BT - ACC 2015 - 2015 American Control Conference

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2015 American Control Conference, ACC 2015

Y2 - 1 July 2015 through 3 July 2015

ER -

Integrated planning, scheduling, and dynamic optimization for sequential batch processes

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