eprintid: 10059096
rev_number: 16
eprint_status: archive
userid: 608
dir: disk0/10/05/90/96
datestamp: 2018-11-09 13:59:24
lastmod: 2021-12-13 03:15:18
status_changed: 2018-11-09 13:59:24
type: article
metadata_visibility: show
creators_name: Aguirre, AM
creators_name: Liu, S
creators_name: Papageorgiou, LG
title: Optimisation approaches for supply chain planning and scheduling under demand uncertainty
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F43
keywords: Supply chain network, Planning and scheduling under
uncertainty, MILP, Model predictive control, Local Search algorithm
note: Copyright © 2018 The Authors. Published by Elsevier B.V. on behalf of Institution of Chemical
Engineers. This is an open access article under the CC BY license (http://creativecommons.
org/licenses/by/4.0/).
abstract: This work presents efficient MILP-based approaches for the planning and scheduling of multiproduct multistage continuous plants with sequence-dependent changeovers in a supply chain network under demand uncertainty and price elasticity of demand. This problem considers multiproduct plants, where several products must be produced and delivered to supply the distribution centres (DCs), while DCs are in charge of storing and delivering these products to the final markets to be sold. A hybrid discrete/continuous model is proposed for this problem by using the ideas of the Travelling Salesman Problem (TSP) and global precedence representation. In order to deal with the uncertainty, we proposed a Hierarchical Model Predictive Control (HMPC) approach for this particular problem. Despite of its efficiency, the final solution reported still could be far from the global optimum. Due to this, Local Search (LS) algorithms are developed to improve the solution of HMPC by rescheduling successive products in the current schedule. The effectiveness of the proposed solution techniques is demonstrated by solving a large-scale instance and comparing the solution with the original MPC and a classic Cutting Plane approach adapted for this work.
date: 2018-10
date_type: published
official_url: https://doi.org/10.1016/j.cherd.2018.08.021
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1591471
doi: 10.1016/j.cherd.2018.08.021
lyricists_name: Liu, Songsong
lyricists_name: Papageorgiou, Lazaros
lyricists_id: SLIUX17
lyricists_id: LPAPA33
actors_name: Papageorgiou, Lazaros
actors_name: Laslett, David
actors_id: LPAPA33
actors_id: DLASL34
actors_role: owner
actors_role: impersonator
full_text_status: public
publication: Chemical Engineering Research and Design
volume: 138
pagerange: 341-357
issn: 0263-8762
citation:        Aguirre, AM;    Liu, S;    Papageorgiou, LG;      (2018)    Optimisation approaches for supply chain planning and scheduling under demand uncertainty.                   Chemical Engineering Research and Design , 138    pp. 341-357.    10.1016/j.cherd.2018.08.021 <https://doi.org/10.1016/j.cherd.2018.08.021>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10059096/1/1-s2.0-S0263876218304155-main.pdf