Optimal path problems are important in many science and engineering fields. Performance criteria may vary in coping with uncertainty, such as expectation, reliability, value at risk, etc. In this paper, we will first summarize our recent work on a dynamic programming based optimal path algorithm...

This paper presents the results of a model of hydrogen production from waste biomass in California. We develop a profit-maximizing model of a biomass hydrogen industry from field to vehicle tank. This model is used to estimate the economic potential for hydrogen production from two waste biomass...

This paper focuses on evaluating the economic potential and infrastructure requirements of hydrogen production from agricultural residues, a representative green energy pathway. A mixed-integer nonlinear programming model is constructed for finding the most efficient and economical configuration...

In this study, a mathematical model that integrates spatial and temporal dimensions is developed for strategic planning of future bioethanol supply chain systems. The planning objective is to minimize the cost of the entire supply chain of biofuel from biowaste feedstock fields to end users over...

A mixed integer stochastic programming model is established to support strategic planning of bioenergy supply chain systems and optimal feedstock resource allocation in an uncertain decision environment. The two-stage stochastic programming model, together with a Lagrange relaxation based...