A novel data-driven rolling horizon production planning approach for the plastic industry under the uncertainty of demand and recycling rate
department or school: Applied Science, Faculty of
department or school: Engineering, School of (Okanagan)
data provider: DSpace
degree campus: UBCO
creator: Larizadeh, Razieh
issued: 2024-07-17T17:55:24Z
issued: 2024
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: Developing an efficient production plan requires considering sustainability practices and the dynamic nature of manufacturing environments. This helps minimize waste to align with sustainability goals, enhance operational efficiency for cost savings, and foster resilience to adapt to market dynamics, thereby ensuring viability. To achieve these goals in the plastic industry, exploring opportunities for recycling integration and adaptability to the uncertain nature of key parameters such as market demand and recycling rate is necessary. The reason stems from the fact that fluctuations in time-varying parameters can pose serious challenges to a predetermined static production plan and make it infeasible in the real world. Furthermore, adhering to sustainability practices is essential to mitigate the detrimental effect of plastic pollution on the ecosystem and to conserve valuable natural resources by decreasing the demand for virgin materials. This thesis develops a novel Data-driven Rolling Horizon Planning (DRHP) approach for a sustainable and dynamic production plan in the plastic industry. In this regard, a dynamic Rolling Horizon (RH) planning framework is formulated as a multi-product, multi-period Mixed Integer Linear Programming (MILP) model. This model aims at minimizing total production costs while taking into account the system’s constraints and sustainability considerations. To deal with uncertainty, the RH-based MILP model is coupled with a Long Short-Term Memory (LSTM) model. The LSTM model leverages historical data of market demand and recycling rate to predict future trends in time-varying parameters and consequently improve the efficiency of the production plan. The outperformance of the proposed DRHP approach is demonstrated through an extensive comparison with a robust static counterpart in terms of total production cost and sustainability measures. Results indicate significant reductions, up to 80%, in production costs using the proposed DRHP appro…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/88654
note: A Novel Data-driven Rolling Horizon Production Planning Approach for the Plastic Industry under the Uncertainty of Demand and Recycling Rate by Razieh Larizadeh B.Sc., Bu-Ali Sina University, 2016 M.Sc., K. N. Toosi University of Technology, 2020 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE COLLEGE OF GRADUATE STUDIES (Mechanical Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) July 2024 © Razieh Larizadeh, 2024ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis entitled: A Novel Data-driven Rolling Horizon Production Planning Approach for the Plastic Industry under the Uncertainty of Demand and Recycling Rate submitted by Razieh Larizadeh in partial fulfillment of the requirements of the degree of Master of Applied Science. Dr. Babak Mohamadpour Tosarkani, School of Engineering Supervisor Dr. Qian Chen, School of Engineering Supervisory Committee Member Dr. Amir Ardestani-Jaafari, Faculty of Management Supervisory Committee Member Dr. Mohammad Hossein Zarifi, School of Engineering University Examiner iii Abstract Developing an efficient production plan requires considering sustainability practices and the dynamic nature of manufacturing environments. This helps minimize waste to align with sustainability goals, enhance operational efficiency for cost savings, and foster resilience to adapt to market dynamics, thereby ensuring viability. To achieve these goals in the plastic industry, exploring opportunities for recycling integration and adaptability to the uncertain nature of key parameters such as market demand and recycling rate is necessary. The reason stems from the fact that fluctuations in time-varying parameters can pose serious challenges to a predetermined static production plan and make it infeasible in the real world. Furthermore, adhering to sustainability practices is essential to mitigate the det…
has type: Thesis/Dissertation
date issued: 2024-09
is shown at: 10.14288/1.0444171
language: eng
degree discipline: Mechanical Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Tosarkani, Babak Mohamadpour
type: Text
identifier URI: http://hdl.handle.net/2429/88654