Dr. Zhiyuan Wang
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Academic Career Length
10Years (2017-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications5 January 2017 in Industrial & Engineering Chemistry Research
Journal Article
Zhiyuan Wang
Gade Pandu RangaiahProcess optimization often has two or more objectives which are conflicting. For such situations, multiobjective optimization (MOO) provides many optimal solutions, which are equally good from the perspective of the given objectives. These solutions, known as Pareto-optimal front and as nondominated solutions, provide deeper insights into the trade-off among the objectives and many choices for implementation. In the past 20 years, researchers have applied MOO to numerous applications in chemical engineering. However, selection of an optimal solution from the set of nondominated solutions has not received much attention in the chemical engineering literature. In the present study, 10 methods for selecting an optimal solution from the Pareto-optimal front are carefully chosen and implemented in an MS Excel-based program. Then, they are applied to the selection of an optimal solution in many benchmark or mathematical problems and chemical engineering applications, and their effectiveness and similarities are analyzed. Results of analysis indicate that, among the 10 methods studied, technique for order of preference by similarity to ideal solution, gray relational analysis, and simple additive weighting are better for choosing one of the Pareto-optimal solutions.
20 July 2020 in Industrial & Engineering Chemistry Research
Journal Article
Zhiyuan WangSPSidharth Sankar Parhi
Sidharth Sankar ParhiGRGade Pandu Rangaiah
Gade Pandu Rangaiah
AJAmiya Jana
Amiya Jana19 April 2023 in Industrial & Engineering Chemistry Research
Journal Article
27 July 2022 in Computers & Chemical Engineering
Journal Article
14 July 2021 in Industrial & Engineering Chemistry Research
Journal Article
Journal Article
Multi-criteria decision making (MCDM) is necessary for choosing one from the available alternatives (or from the Pareto-optimal solutions obtained by multi-objective optimization), where the performance of each alternative is quantified against several criteria (or objectives). This paper presents a comprehensive review of the application of MCDM methods in chemical and process engineering. It systematically outlines the essential steps in MCDM including the various normalization, weighting, and MCDM methods that are critical to decision making. The review draws on published papers identified through a search in the Scopus database, focusing on works by authors with more contributions to the field and on highly cited papers. Each selected paper was analyzed based on the MCDM, normalization, and weighting methods used. Additionally, this paper introduces two readily available programs for performing MCDM calculations. In short, it provides insights into the MCDM steps and methods, highlights their applications in chemical and process engineering, and discusses the challenges and prospects in this area.
About Me
Dr. Zhiyuan Wang is a Lecturer at Singapore University of Social Sciences (SUSS, the sixth autonomous university in Singapore), where he teaches in the Finance Programme within the School of Business. Prior to this, he served as an Assistant Professor at DigiPen Institute of Technology, teaching in the Computer Science Programme and the Technology in Finance Immersion Programme. He holds a Ph.D. from National University of Singapore (NUS), an M.Sc. from Nanyang Technological University (NTU), and a B.Eng. from NUS.
Dr. Wang’s research interests lie in computing algorithms, fintech, optimization in finance, machine learning, deep learning, multi-criteria decision-making, and multi-objective optimization. He has published more than 18 journal articles (SCIE Q1/Q2) and book chapters in these fields, as well as two authored books: Numerical Machine Learning (ISBN 9789815136982) and Multi-Criteria Decision-Making: Principles, Methods and Programs (ISBN 9781032853635). The full list of his publications can be found on Google Scholar.
In addition, Dr. Wang serves as an Associate Editor for Innovation and Emerging Technologies, an Editorial Board Member of Journal of Intelligent Management Decision, and as a Guest Editor for multiple MDPI journals (e.g., Mathematics, Systems). Further details can be found on Dr. Wang’s personal webpage.