This program has many weighting and selection methods for ranking non-dominated (Pareto-optimal) solutions obtained by multi-objective optimization. For more details, see (a) Wang Z., Parhi S.S., Rangaiah G.P. and Jana A.K., Analysis of Weighting and Selection Methods for Pareto-optimal Solutions of Multi-Objective Optimization in Chemical Engineering Applications, Industrial & Engineering Chemistry Research, in press (2020) and (b) Wang Z. and Rangaiah G.P., Application and Analysis of Methods for Selecting an Optimal Solution from the Pareto-Optimal Front obtained by Multi-Objective Optimization, Industrial & Engineering Chemistry Research, 56, 560-574 (2017).  

Excel-based Multi-Objective Optimization program (in Excel and VBA) based on the elitist non-dominated sorting genetic algorithm. For more details, see Sharma, Rangaiah and Cheah, Multi-objective optimization using MS Excel with an application to design of a falling-film evaporator system, Food and Bioproducts Processing, 90(2), 123-134 (2011).

Excel-based Multi-Objective Optimization program (in Excel and VBA) based on integrated/improved multi-objective differential evolution. For more details, see Sharma and Rangaiah, An improved multi-objective differential evolution with a termination criterion for optimizing chemical processes, Computers and Chemical Engineering, 56, 155-173 (2013).

This MS Excel program computes performance metrics (namely, generational distance, inverse generational distance, convergence metric and spread) of a given set of non-dominated solutions. It requires true Pareto-optimal front. For more details, see Sharma S., Rangaiah G. P. and Marechal F. (2017), Multi-objective Optimization Programs and Their Application to Amine Absorption Process Design for Natural Gas Sweetening, In Rangaiah G. P. (editor), Multi-objective Optimization: Techniques and Applications in Chemical Engineering (2nd Ed.), World Scientific, Singapore.

This MS Excel program performs sorting of given solutions to find the set of non-dominated solutions. For more details, see Sharma S., Rangaiah G. P. and Marechal F. (2017), Multi-objective Optimization Programs and Their Application to Amine Absorption Process Design for Natural Gas Sweetening, In Rangaiah G. P. (editor), Multi-objective Optimization: Techniques and Applications in Chemical Engineering (2nd Ed.), World Scientific, Singapore.

Novel Bare-Bones Particle Swarm Optimization (in Excel and VBA) for global optimization. For more details, see Zhang, Kennedy, Rangaiah and Bonilla-Petriciolet, Novel bare-bones particle swarm optimization and its performance for modelling vapour–liquid equilibrium data, Fluid Phase Equilibria, 301, 33-45 (2011).

Two versions of Differential Evolution with Tabu List (in FORTRAN) for global optimization. For more details, see Chapter 14 in Rangaiah, Stochastic Global Optimization: Techniques and Applications in Chemical Engineering, World Scientific (2010).

Capital Cost Estimation Program (in Excel and VBA) using the cost correlations in Seider, Seader and Widagdo, Product and Process Design Principles: Synthesis, Analysis and Evaluation, Wiley (2010). For more details, see Feng and Rangaiah, Evaluating Capital Cost Estimation Programs, Chemical Engineering, August (2011).

Detailed Factorial Program for capital cost estimation (in Excel and VBA) using the cost correlations in Sinnott and Towler, Chemical Engineering Design, Butterworth (2009). For more details, see Feng and Rangaiah, Evaluating Capital Cost Estimation Programs, Chemical Engineering, August (2011). 

Aspen HYSYS steady-state simulation file for the styrene monomer plant. For more details, see Vasudevan, Rangaiah, Konda and Tay, Application and Evaluation of Three Methodologies for Plant-Wide Control of the Styrene Monomer Plant. Ind. Eng. Chem. Res., 48, 10941-10961 (2009).