Mathematical optimisation model for management of sago palm plantation expansions

Jaya Prasanth Rajakal, Denny K. S. Ng, Raymond R. Tan, Viknesh Andiappan, Yoke Kin Wan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
57 Downloads (Pure)


Sago palm is an important indigenous crop grown in Southeast Asia. Its main product, sago starch, has the potential to be an alternative source of starch when compared to traditional starch derived from maize, sweet potato, cassava etc. Despite its potential, sago has remained as wild forest trees in swampy areas and unutilised for decades. Recently, Malaysia and Indonesia have shown interest in establishing estate plantations of sago palms. Although such a development may be welcomed, it is advisable to exercise caution during expansion of sago plantations. It is highly likely that unplanned expansions may result in large scale clearing of the tropical and peatland forests that are densely concentrated. In this respect, the vulnerability of these sensitive ecosystems during sago plantation expansions must be carefully accounted for. Therefore, in order to ensure planned and minimal sago plantation expansion, decision support tools that help to strategies land use changes (LUC) is crucial. Thus, this work presents a mathematical optimisation model of the type mixed integer linear programming (MILP) to plan for sago plantation expansions. The proposed model determines whether land expansion would be required when demands increase, accounting for the cost involved in expansion. A simple sago value chain has been solved to illustrate the proposed model. The results show that the optimised results avoided 4.3 % - 9.3 % of possible land area under expansion; 2.96 – 4.05 times of CO2 emission and 120.16 % - 189.14 % of cost savings.

Original languageEnglish
Pages (from-to)109-114
Number of pages6
JournalChemical Engineering Transactions
Publication statusPublished - 1 Feb 2020

ASJC Scopus subject areas

  • General Chemical Engineering


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