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

Authored by Sojung Kim, Sumin Kim, James R Kiniry

Date Published: 2018

DOI: 10.1016/j.simpat.2018.05.006

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts Pseudocode

Model Code URLs: Model code not found

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 (R) with geographic information system (GIS). The OptQuese (R) 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.

Tags

Agent-based modeling Management bioenergy renewable energy Energy switchgrass Yield Grasses Almanac Location-allocation Network partitioning Biomass storage Biofuel supply chain Southern great-plains Diverse sites Almanac model