This article describes the key challenges and opportunities in modeling and optimization of
biomass-to-bioenergy supply chains. It reviews the major energy pathways from terrestrial …

Following the scarcity of resources, rising energy prices, and an increasing awareness of the
role manufacturing plays in the generation of greenhouse gas emissions, the consumption …

A novel data‐driven adaptive robust optimization framework that leverages big data in
process industries is proposed. A Bayesian nonparametric model—the Dirichlet process …

Recent interest in biomass supply chain management has stimulated research efforts in the
industry and academic communities. Techno-economic modeling and optimization efforts …

The optimal design and operations of water supply chain networks for shale gas production
is addressed. A mixed‐integer linear fractional programming (MILFP) model is developed …

A novel data‐driven approach for optimization under uncertainty based on multistage
adaptive robust optimization (ARO) and nonparametric kernel density M‐estimation is …

Global optimization for sustainable design and synthesis of a large‐scale algae processing
network under economic and environmental criteria is addressed. An algae processing …

With the increasing energy price, the rapid growth of electricity demand and severe
challenges for sustainable development, energy-efficient scheduling is becoming more and …

In this work, we propose a novel multiobjective optimization model for the sustainable
design and operation of bioelectricity supply chain networks, which simultaneously accounts …

This paper addresses the sustainable design and synthesis of manufacturing processes for
making algal bioproducts. We propose by far the most comprehensive superstructure …