Multi-objective Bonobo optimisers of industrial low-density polyethylene reactor

• Published in: CHEMICAL PRODUCT AND PROCESS MODELING
• Main Authors: Rohman, Fakhrony Sholahudin; Alwi, Sharifah Rafidah Wan; Muhammad, Dinie; Zahan, Khairul Azly; Murat, Muhamad Nazri; Azmi, Ashraf
• Format: Article; Early Access
• Language: English
• Published: WALTER DE GRUYTER GMBH 2024
• Subjects: Engineering
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001280385900001
• ISSN: 1934-2659; 2194-6159
• DOI: 10.1515/cppm-2024-0023

A multi-objective optimization (MOO) technique to produce a low-density polyethylene (LDPE) is applied to address these two problems: increasing conversion and reducing operating cost (as the first optimization problem, P1) and increasing productivity and reducing operating cost (as the second optimization problem, P2). ASPEN Plus software was utilized for the model-based optimization by executing the MOO algorithm using the tubular reactor model. The multi-objective optimization of multi-objective Bonobo optimisers (MOBO-I, MOBO-II and MOBO-III) are utilised to solve the optimization problem. The performance matrices, including hypervolume, pure diversity, and distance, are used to decide on the best MOO method. An inequality constraint was introduced on the temperature of the reactor to prevent run-away. According to the findings of the study, the MOBO-II for Problems 1 and 2 was the most effective MOO strategy. The reason is that the solution set found represents the most accurate, diversified, and acceptable distribution points alongside the Pareto Front (PF) in terms of homogeneity. The minimum operating cost, the maximum conversion and productivity obtained by MOBO-II are Mil. RM/year 114.3, 31.45 %, Mil. RM/year 545.3, respectively.