Optimal Control of Continuous Casting by Nondifferentiable Multiobjective Optimization
Computational Optimization and Applications
Interactive multiobjective optimization system WWW-NIMBUS on the internet
Computers and Operations Research - Special issue on artificial intelligence and decision support with multiple criteria
Numerical Comparison of Some Penalty-Based Constraint Handling Techniques in Genetic Algorithms
Journal of Global Optimization
Introduction to Multiobjective Optimization: Interactive Approaches
Multiobjective Optimization
IEEE Transactions on Evolutionary Computation
Wastewater treatment: New insight provided by interactive multiobjective optimization
Decision Support Systems
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Dynamic process simulators for plant-wide process simulation and multiobjective optimization tools can be used by industries as a means to cut costs and enhance profitability. Specifically, dynamic process simulators are useful in the process plant design phase, as they provide several benefits such as savings in time and costs. On the other hand, multiobjective optimization tools are useful in obtaining the best possible process designs when multiple conflicting objectives are to be optimized simultaneously. Here we concentrate on interactive multiobjective optimization. When multiobjective optimization methods are used in process design, they need an access to dynamic process simulators, hence it is desirable for them to coexist on the same software platform. However, such a co-existence is not common. Hence, users need to couple multiobjective optimization software and simulators, which may not be trivial. In this paper, we consider APROS, a dynamic process simulator and couple it with IND-NIMBUS, an interactive multiobjective optimization software. Specifically, we: (a) study the coupling of interactive multiobjective optimization with a dynamic process simulator; (b) bring out the importance of utilizing interactive multiobjective optimization; (c) propose an augmented interactive multiobjective optimization algorithm; and (d) apply an APROS-NIMBUS coupling for solving a dynamic optimization problem in a two-stage separation process.