A simulation-based robust biofuel facility location model for an integrated bio-energy logistics network

Abstract

Abstract:Purpose: The purpose of this paper is to propose a simulation-based robust biofuel facility location model for solving an integrated bio-energy logistics network (IBLN) problem, where biomass yield is often uncertain or difficult to determine.Design/methodology/approach: The IBLN considered in this paper consists of four different facilities: farm or harvest site (HS), collection facility (CF), biorefinery (BR), and blending station (BS). Authors propose a mixed integer quadratic modeling approach to simultaneously determine the optimal CF and BR locations and corresponding biomass and bio-energy transportation plans. The authors randomly generate biomass yield of each HS and find the optimal locations of CFs and BRs for each generated biomass yield, and select the robust locations of CFs and BRs to show the effects of biomass yield uncertainty on the optimality of CF and BR locations. Case studies using data from the State of South Carolina in the United State are conducted to demonstrate the developed model's capability to better handle the impact of uncertainty of biomass yield. Findings:The results illustrate that the robust location model for BRs and CFs works very well in terms of the total logistics costs. The proposed model would help decision-makers find the most robust locations for biorefineries and collection facilities, which usually require huge -1415-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.1196 investments, and would assist potential investors in identifying the least cost or important facilities to invest in the biomass and bio-energy industry.Originality/value: An optimal biofuel facility location model is formulated for the case of deterministic biomass yield. To improve the robustness of the model for cases with probabilistic biomass yield, the model is evaluated by a simulation approach using case studies.The proposed model and robustness concept would be a very useful tool that helps potential biofuel investors minimize their investment risk.

Towards facing uncertainties in biofuel supply chain networks: a systematic literature review

“…Then, they employed the Monte Carlo simulation to investigate the effect of input parameters (mainly the product prices) on the obtained results. Hong et al ( 2014 ) investigated a robust optimization model based on the simulation technique to determine the location of biofuel facilities and transportation decisions in a bio-energy logistics network when biomass yield acts as the uncertain parameter. To incorporate different types of uncertainty in a rice straw-based BSC, Diehlmann et al ( 2019 ) proposed a hybrid simulation–optimization framework where technological and economic uncertainties were involved in a Monte Carlo simulation.…”