De La Salle University

About: De La Salle University is a education organization based out in Manila, Philippines. It is known for research contribution in the topics: Population & Computer science. The organization has 2951 authors who have published 4374 publications receiving 49567 citations. The organization is also known as: Pamantasang De La Salle.

A vulnerability index for post-disaster key sector prioritization

Abstract: Input–output-based techniques have proven to be effective in modeling how disasters lead to economic disruptions, while taking into account the structural connectivity of economic systems. In particular, through the inoperability input–output model (IIM), the degree of failure in an economic system can be quantified on a scale from 0 (normal state) to 1 (complete failure). This paper develops a vulnerability index that builds upon the foundations of the Leontief input–output model and the IIM, which is capable of identifying and prioritizing the key sectors in the aftermath of disasters. The key sector prioritization framework proposed in this paper is expected to contribute to the domain of disaster preparedness planning, such as enhancing the efficiency of resource allocation across various sectors. The proposed vulnerability index is formulated in terms of three underlying components: (1) economic impact, (2) propagation length, and (3) sector size. The vulnerability index captures the impact of invest...

Prospects and challenges for chemical process synthesis with P-graph

Abstract: The P-graph framework was developed to solve Process Network Synthesis (PNS) problems in plant design. It provides a powerful engineering toolbox based on the constituent Maximal Structure Generation (MSG), Solution Structure Generation (SSG) and Accelerated Branch-and-Bound (ABB) algorithms. During the four decades of its development, the P-graph framework has proven to be capable of solving various engineering applications framed as PNS problems. This review paper gives a survey of the development of the P-graph framework, with emphasis on its enhancements and the diversification of applications in process engineering. Research gaps and promising directions for P-graph research are then discussed.