G
Gade Pandu Rangaiah
Researcher at National University of Singapore
Publications - 282
Citations - 6739
Gade Pandu Rangaiah is an academic researcher from National University of Singapore. The author has contributed to research in topics: Multi-objective optimization & Global optimization. The author has an hindex of 42, co-authored 277 publications receiving 5737 citations. Previous affiliations of Gade Pandu Rangaiah include Indian Institute of Technology Kanpur & Nanyang Technological University.
Papers
More filters
Journal ArticleDOI
Evaluation of two termination criteria in evolutionary algorithms for multi-objective optimization of complex chemical processes
TL;DR: This study investigates two termination criteria based on search progress, for MOO of three complex chemical processes modeled by process simulators, namely, Aspen Plus and Aspen HYSYS, and finds Chi-Squared test based Termination Criterion (CSTC) is more reliable and terminates the search earlier, thus reducing computational time substantially.
Journal ArticleDOI
A Comprehensive Evaluation of PID, Cascade, Model-Predictive, and RTDA Controllers for Regulation of Hypnosis†
TL;DR: In this article, the performance of single-loop PID, cascade, model-predictive, and RTDA controllers for closed-loop regulation of hypnosis using isoflurane with bispectral index (BIS) as the controlled variable.
Journal ArticleDOI
Integrated Framework Incorporating Optimization for Plant-Wide Control of Industrial Processes
TL;DR: An integrated methodology is proposed in this paper that incorporates heuristics and optimization, together with the use of simulation throughout the procedure, for plant-wide control of industrial processes.
Journal ArticleDOI
Vapor recompressed batch distillation: Optimizing reflux ratio at variable mode
TL;DR: This work aims at optimizing a vapor recompressed batch distillation that runs at variable reflux mode by employing a multi-objective optimization (MOO) strategy by employing the factorial analysis for identifying dominating variables and the elitist non-dominated sorting genetic algorithm.