eprintid: 10194769
rev_number: 9
eprint_status: archive
userid: 699
dir: disk0/10/19/47/69
datestamp: 2024-08-19 10:08:37
lastmod: 2024-08-20 10:14:03
status_changed: 2024-08-19 10:08:37
type: book_section
metadata_visibility: show
sword_depositor: 699
creators_name: Nikkhah, Hasan
creators_name: Charitopoulos, Vassilis M
creators_name: Avraamidou, Styliani
creators_name: Beykal, Burcu
title: Bilevel optimization of mixed-integer nonlinear integrated planning and scheduling problems using the DOMINO framework
ispublished: pub
divisions: UCL
divisions: B04
divisions: F43
keywords: Data-driven optimization, mixed-integer nonlinear programming, bilevel
programming, enterprise-wide optimization, production planning, scheduling.
note: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: We study the solution of integrated planning and scheduling problems that are formulated as bilevel programming problems with mixed-integer nonlinear lower levels using data-driven optimization algorithms. Due to their inherent interdependence, multi-scale nature, and volatile market conditions, decision-making in such multi-level supply chain networks poses challenging task. Traditionally, these problems are addressed sequentially but, this approach often results in production schedules that are not feasible. Motivated by this, we formulate enterprise-wide decision-making problems with linear production planning and mixed-integer nonlinear scheduling level as a bilevel optimization problem. We solve the resulting integrated problem using the DOMINO framework which is a data-driven optimization strategy to handle general constrained bilevel optimization problems. We demonstrate our approach on case studies with varying complexities from crude oil scheduling using a continuous-time formulation to scheduling of continuous manufacturing processes using a traveling salesman problem formulation. The results show that DOMINO can address bilevel programming problems with high-dimensional mixed-integer nonlinear lower levels and can be applied to complex integrated enterprise-wide optimization problems, regardless of the lower-level formulation type.
date: 2024
date_type: published
publisher: Elsevier
official_url: http://dx.doi.org/10.1016/b978-0-443-28824-1.50319-7
full_text_type: pub
language: eng
verified: verified_manual
elements_id: 2295368
doi: 10.1016/B978-0-443-28824-1.50319-7
isbn_13: 9780443288241
lyricists_name: Charitopoulos, Vasileios
lyricists_id: VCHAR89
actors_name: Charitopoulos, Vasileios
actors_id: VCHAR89
actors_role: owner
full_text_status: restricted
series: Computer Aided Chemical Engineering
volume: 53
place_of_pub: Amsterdam, The Netherlands
pagerange: 1909-1914
book_title: Computer Aided Chemical Engineering
editors_name: Manenti, Flavio
editors_name: Reklaitis, Gintaras V
citation:        Nikkhah, Hasan;    Charitopoulos, Vassilis M;    Avraamidou, Styliani;    Beykal, Burcu;      (2024)    Bilevel optimization of mixed-integer nonlinear integrated planning and scheduling problems using the DOMINO framework.                    In: Manenti, Flavio and Reklaitis, Gintaras V, (eds.) Computer Aided Chemical Engineering. (pp. 1909-1914).   Elsevier: Amsterdam, The Netherlands.      
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10194769/1/617Nikkhah.pdf