A biobjective chance constrained optimization model to evaluate the economic and environmental impacts of biopower supply chains

Stochastic techno-economic evaluation model for biomass supply chain: A biomass gasification case study with supply chain uncertainties

“…Apart from the probabilistic results shown in Figs. [16][17][18][19], the utility stream also produces NO x and SO x during the combustion process for coal and gas. Both NO x and SO x have acidification potential (AP) that ultimately sum up to a total annual equivalent emission of 233.8 kg SO 2, eq .…”

“…This, therefore, causing a variation in terms of the overall costs. Other than that, Karimi et al [17] developed a bi-objective chance constrained optimization model to evaluate the economic and environmental performance of a given biopower supply chain. Within the model developed, the authors modelled the biomass quality (moisture content and energy content of biomass) randomly via a probability distribution.…”

Toward a Sustainable Municipal Solid Waste Incineration Fly-Ash Utilization Network: Integrating Hybrid Life Cycle Assessment with Multiobjective Optimization

“…The application of MOO in the design of the IFA utilization network can be inspired by the existing studies on manufacturing process improvements , and system optimization. , Since multiple objectives were considered in MOO problems, there are bound to be trade-offs and win-win solutions, which can be quantified using Pareto-optimal solutions found by the ε-constraint method. , While extremely insightful, most existing studies integrating PLCA with MOO were impeded in investigating environmental impacts extending to the whole economic system. However, there are only very few studies that fully capture LCI data using the HLCA method within a MOO framework. , As a pioneer, Bakshi et al , developed an integrated matrix formulation that applies HLCA to sustainable process design problems.…”

“…41,42 Since multiple objectives were considered in MOO problems, there are bound to be trade-offs and win-win solutions, which can be quantified using Pareto-optimal solutions found by the ε-constraint method. 43,44 While extremely insightful, most existing studies integrating PLCA with MOO were impeded in investigating environmental impacts extending to the whole economic system. However, there are only very few studies that fully capture LCI data using the HLCA method within a MOO framework.…”