Problem structuring methods | EPFL Graph Search

Problem structuring methods (PSMs) are a group of techniques used to model or to map the nature or structure of a situation or state of affairs that some people want to change. PSMs are usually used by a group of people in collaboration (rather than by a solitary individual) to create a consensus about, or at least to facilitate negotiations about, what needs to change. Some widely adopted PSMs include soft systems methodology, the strategic choice approach, and strategic options development and analysis (SODA). Unlike some problem solving methods that assume that all the relevant issues and constraints and goals that constitute the problem are defined in advance or are uncontroversial, PSMs assume that there is no single uncontested representation of what constitutes the problem. PSMs are mostly used with groups of people, but PSMs have also influenced the coaching and counseling of individuals. History The term "problem structuring methods

Modeling Supply Chain Disruptions: A Network Flow Approach

René Yves Glogg

Globalization, outsourcing and cost optimization have all contributed to increased supply chain vulnerability, yet our understanding of effective mitigation strategies remains limited. In our research, we study the effects of disruptions on supply chain networks. To do so, we develop in the first research project a bilevel optimization model to analyze supply chain disruptions in a production setting. This results in a convex network flow problem in which total production cost is minimized under a chance constraint. This chance constraint imposes a bound on the regret of disrupted scenarios with high pre-determined probability, where this regret is defined as a cost surplus which results from a comparison between a reactive setting, where we consider the disruption unknown until it occurs, and an anticipative setting, which assumes the disruption scenario to be known at the beginning of the planning horizon. A generalized Benders decomposition approach which makes use of the problem structure is developed to solve the problem efficiently. In the second research project we study a similar model in which an additional chance constraint on service level is introduced to account for demand uncertainty. We derive an approximation of this model and derive a bound on the approximation error. This approximation model is then solved with the same Benders decomposition procedure as the first model discussed. We obtain managerial insights from both models by means of numerical experimentation. We demonstrate a relationship between the stochastic demand and service level requirements. Moreover, we observe that unused production capacity is a key driver for mitigation inventory. In the last research project we shift our focus towards gaining a more holistic understanding of the supply chain network disruption literature. The number of articles written in the area has increased significantly in the last few years, and with the advent of the Covid-19 pandemic the interest in the area has expanded even further. We perform a literature review with a particular focus on recognizing research gaps. We observe a surprising lack of articles studying assembly supply chains, despite their ubiquity in real world applications. A similar lack of articles is observed in the area of multi-product supply chains as well. Finally, in light of the ongoing Covid-19 pandemic we shift our attention towards the disruptive effect of pandemics on supply chains. We observe that most of the mathematical models of supply chain networks under disruptions discussed in the literature are incapable of accounting for the fact that pandemics disrupt several aspects of supply chain networks simultaneously. Moreover, we observe that a large number of articles studies problems stemming directly from real world applications. The resulting models are often challenging to solve mathematically, so we perform a comprehensive study of solution methods used in the supply chain network literature and highlight multi-objective optimization as an area of utmost importance for current and future research.

EPFL2021

Preparation of Highly Porous Metal-Organic Framework Beads for Metal Extraction from Liquid Streams

Hassan Abedini, Anita Justin, Ilia Kochetygov, Guanchu Lu, Emadeddin Oveisi, Li Peng, Wendy Lee Queen, Daniel Teav Sun, Olga Syzgantseva, Olga Trukhina, Shuliang Yang

Metal-organic frameworks (MOFs) offer great promise in a variety of gas- and liquid-phase separations. However, the excellent performance on the lab scale hardly translates into pilot- or industrial-scale applications due to the microcrystalline nature of MOFs. Therefore, the structuring of MOFs into pellets or beads is a highly solicited and timely requirement. In this work, a general structuring method is developed for preparing MOF-polymer composite beads based on an easy polymerization strategy. This method adopts biocompatible, biodegradable poly(acrylic acid) (PAA) and sodium alginate monomers, which are cross-linked using Ca2+ ions. Also, the preparation procedure employs water and hence is nontoxic. Moreover, the universal method has been applied to 12 different structurally diverse MOFs and three MOF-based composites. To validate the applicability of the structuring method, beads consisting of a MOF composite, namely Fe-BTC/PDA, were subsequently employed for the extraction of Pb and Pd ions from real-world water samples. For example, we find that just 1 g of Fe-BTC/PDA beads is able to decontaminate >10 L of freshwater containing highly toxic lead (Pb) concentrations of 600 ppb while under continuous flow. Moreover, the beads offer one of the highest Pd capacities to date, 498 mg of Pd per gram of composite bead. Furthermore, large quantities of Pd, 7.8 wt %, can be readily concentrated inside the bead while under continuous flow, and this value can be readily increased with regenerative cycling.

AMER CHEMICAL SOC2020

Modeling Supply Chain Disruptions: A Network Flow Approach

René Yves Glogg

EPFL2021