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The optimization approach is well established in both academia and in industrial practice with numerous applications in chemical engineering. Several tools are readily available for process optimization. However, optimization applications often have more than one objective, which requires Multi-Objective Optimization (MOO). Since the early 2000s, MOO has grown significantly as an effective and useful approach, especially for process optimization in chemical engineering. In particular, current technologies and requirements in the petrochemical, chemical, biotechnology, energy and other emerging industries have imposed new challenges to the field of MOO. These challenges are due to the necessity of solving complex design-optimization problems that involve several objectives, many decision variables and constraints. To date, there have been many theoretical and computational developments in MOO and its …