Metaheuristics in process engineering: A historical perspective

Abstract

This chapter presents an overview of applications of metaheuristics to solve different real-world chemical process engineering problems over the last 30 years. The first part of this chapter describes some fundamental characteristics of metaheuristics, a class of global stochastic methods and also provides the standard description of some of the most widely used metaheuristics such as simulated annealing, tabu search, genetic algorithms, and ant colony optimization (ACO). In the second part, different practical applications of these metaheuristics related to chemical process industry are covered such as heat exchanger networks (HENs), short-term scheduling of batch processes, dynamic optimization of chemical and biochemical processes, parameter estimation, and multiobjective optimization with extensive list of references.