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A Stochastic Optimisation Model for Biomass Outsourcing in Cement Manufacturing Industry with Production Planning Constraints

Lookup NU author(s): Professor Jingxin DongORCiD, Professor Christian Hicks



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


It is estimated that 12-15% of total global industrial energy is consumed by the Cement Manufacturing Industry (CMI). To improve environmental sustainability, biomass has been used as an alternative to fossil fuels. There is a comprehensive literature on biomass production and conversion, but little attention has been paid to biomass logistics in the cement industry. We propose the use of cement distribution trucks to collect biomass on their return journeys. Compared with the use of specialist biomass suppliers, the collection of biomass via cement distribution networks has greater uncertainties in delivery times, volume and quality. This is because biomass collection is a secondary activity and is subject to cement order quantities and the random geographical locations of cement customers. To cope with these uncertainties, additional on-site storage and handling equipment is required. This paper proposes a stochastic programming model to measure the cost-effectiveness of collecting biomass using return cement distribution trucks in comparison with purchasing biomass from specialised biomass suppliers. A numerical experiment based on a real-word dataset has been conducted to verify the effectiveness of the developed model. It is shown that the use of cement distribution networks is more cost effective than using specialised suppliers.

Publication metadata

Author(s): Abriyantoroa D, Dong J, Hicks C, Singh SP

Publication type: Article

Publication status: Published

Journal: Energy Journal

Year: 2019

Volume: 169

Issue: 15

Pages: 515-526

Print publication date: 15/02/2019

Online publication date: 03/12/2018

Acceptance date: 25/11/2018

Date deposited: 25/11/2018

ISSN (print): 0360-5442

ISSN (electronic): 1873-6785

Publisher: International Association for Energy Economics


DOI: 10.1016/


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