Authors: G. P. Rangaiah and S. Sharma
Optimization has been successfully applied to improve the performance of processes and systems in diverse areas such as engineering, science and business. It also plays an important role in establishing models for physical phenomena and processes. The goal of optimization is to find the values of suitable decision variables, which maximize or minimize the specified performance criterion and simultaneously satisfy constraints. In most of the application problems, there are a number of objective functions (e.g., conversion, selectivity, profit, energy and environmental impact), and these may be conflicting in nature. Traditionally, only one of these objectives is chosen and optimization is performed; this can be referred to as single objective optimization (SOO). However, it is often desirable to consider several objectives of interest. Multi-objective optimization (MOO), as the name implies, can solve problems having more than one objective. It provides many optimal solutions, showing the trade-off among different objectives, and also the corresponding values of decision variables. The use of MOO by researchers in scientific investigations has been increasing, particularly in the last 10-15 years.
Keywords: multi-objective optimization; chemical engineering; fermentation process; cumene process.