Pareto-optimal solutions for multicriteria optimization of a chemical engineering process using a diploid genetic algorithm

Abstract

In many, if not most, optimization problems, industrialists are often confronted with multi-objective decision problems. For example, in manufacturing processes, it may be necessary to optimize several criteria to take into account all the market constraints. Hence, the purpose is to choose the best trade-offs among all the defined and conflicting objectives. This paper presents a multi-objective optimization procedure based on a diploid genetic algorithm, which yields an optimal zone containing the solution under the concept of Pareto dominance. Pair-wise points are compared, and non-dominated points are collected in the Pareto region. Then a ranking is established, and the decision maker selects the first-best solution. Finally, the procedure is applied to the chemical engineering process of cattle feed manufacture. © 2017 Wiley. All rights reserved.