Design, Analysis and Operations under Uncertainty I

Complex processes in physics, chemistry, biology, engineering and finance, often exhibit uncertainties, or fluctuations, or noises, in their structures as a rule rather than as an exception. To interpret, analyze, model and simulate these uncertainties, algorithms have developed to yield not only the structure or pattern of these processes, but also the statistical characteristics of the evolutions of underlined uncertainties that the conventional deterministic models can not offer. These algorithms have significantly optimized process design and operations. Recent development seems to suggest the needs for efficient solution of large-scale problems and the applicability of the proposed methodologies in realistic case studies. Papers are sought that describe: (i) modeling, algorithmic development and solution procedures for the design and operation under uncertainty, (ii) characterization of system behavior under uncertainty, (iii) evaluation of feasible region of design operation for realistic nonconvex cases, (iv) integration of uncertainty analysis within process design and operations in a unified framework, and (v) reconciliations of the stochastic algorithms developed by engineers with those by chemical physicists.