Two-phase simulation-based location-allocation optimization of biomass storage distribution

Sojung Kim, Sumin Kim, James R. Kiniry

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

This study presents a two-phase simulation-based framework for finding the optimal locations of biomass storage facilities that is a very critical link on the biomass supply chain, which can help to solve biorefinery concerns (e.g. steady supply, uniform feedstock properties, stable feedstock costs, and low transportation cost). The proposed framework consists of two simulation phases: (1) crop yield estimation using a process-based model such as Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) and (2) biomass transportation cost estimation using agent-based simulation (ABS) such as AnyLogic® with geographic information system (GIS). The OptQuest® in AnyLogic is used as an optimization engine to find the best locations of biomass storage facilities based on evaluation results given by the two-phase simulation framework. In addition, network partitioning and integer linear programming techniques are used to mitigate computation demand of the optimization problem. Since the proposed hybrid simulation approach utilizes realistic biofuel feedstock production and considers dynamics of supply chain activities, it is able to provide reliable locations of biomass storage facilities for operational excellence of a biomass supply chain.

Original languageEnglish
Pages (from-to)155-168
Number of pages14
JournalSimulation Modelling Practice and Theory
Volume86
DOIs
StatePublished - Aug 2018

Keywords

  • Agent-based modeling
  • ALMANAC
  • Biomass storage
  • Location-allocation
  • Network partitioning
  • Renewable energy

Fingerprint

Dive into the research topics of 'Two-phase simulation-based location-allocation optimization of biomass storage distribution'. Together they form a unique fingerprint.

Cite this