Tsan Sheng Ng

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We propose a class of functions, called multiple objective satisficing (MOS) criteria, for evaluating the level of compliance of a set of objectives in meeting their targets collectively under uncertainty. The MOS criteria include the targets’ achievement probability (success probability criterion) as a special case and also extend to situations when the(More)
Elucidating the dynamics of national labor trends is a highly complex problem, as the labor market system is an interaction and interrelation of many variables and subsystems. To understand firm behavior and hence enable effective policy making, one must adopt a systems thinking and evolutionary approach to study the interplay of these forces and systems.(More)
To compress research and development (R&D) cycle times of high-tech mechatronic products with conformance performance metrics, managing R&D projects to allow engineers from electrical, mechanical, and manufacturing disciplines receive real-time design feedback and assessment are essential. In this paper, we propose a systems design procedure to integrate(More)
a r t i c l e i n f o In this work we develop a new approach to study the energy import resilience of an economy using linear programming and economic input–output analysis. In particular, we propose an energy import resilience index by examining the maximum level of energy import reduction that the economy can endure without sacrificing domestic demands. A(More)
Satisficing, as an approach to decision-making under uncertainty, aims at achieving solutions that satisfy the problem’s constraints as well as possible. Mathematical optimization problems that are related to this form of decision-making include the P-model of Charnes and Cooper (1963), where satisficing is the objective, as well as chance-constrained and(More)
The human behavior aspect of pandemic prevention and mitigation involve uncertainties manifested as a range of responses, from the extreme to the indifferent. Relationships between variables influencing human behavior are usually described qualitatively, and as such do not suffice for stock and flow models. These uncertainties can slow down the modelling(More)