Sarkar Tanmay, Salauddin Molla, Mukherjee Alok, Shariati Mohammad Ali, Rebezov Maksim, Tretyak Lyudmila, Pateiro Mirian, Lorenzo José M
Department of Food Processing Technology, Malda Polytechnic, West Bengal State Council of Technical Education, Malda, 732102, West Bengal, India.
Department of Food Processing Technology, Mir Madan Mohanlal Govt. Polytechnic, West Bengal State Council of Technical Education, Nadia 741156, West Bengal, India.
Curr Res Food Sci. 2022 Feb 16;5:432-450. doi: 10.1016/j.crfs.2022.02.006. eCollection 2022.
Bio-inspired optimization techniques (BOT) are part of intelligent computing techniques. There are several BOTs available and many new BOTs are evolving in this era of industrial revolution 4.0. Genetic algorithm, particle swarm optimization, artificial bee colony, and grey wolf optimization are the techniques explored by researchers in the field of food processing technology. Although, there are other potential methods that may efficiently solve the optimum related problem in food industries. In this review, the mathematical background of the techniques, their application and the potential microbial-based optimization methods with higher precision has been surveyed for a complete and comprehensive understanding of BOTs along with their mechanism of functioning. These techniques can simulate the process efficiently and able to find the near-to-optimal value expeditiously.
生物启发式优化技术(BOT)是智能计算技术的一部分。有多种可用的BOT,并且在工业4.0时代有许多新的BOT正在不断发展。遗传算法、粒子群优化、人工蜂群和灰狼优化是食品加工技术领域研究人员探索的技术。尽管如此,还有其他潜在方法可以有效解决食品工业中的最优相关问题。在这篇综述中,对这些技术的数学背景、它们的应用以及具有更高精度的潜在基于微生物的优化方法进行了调查,以便全面、综合地了解BOT及其运作机制。这些技术可以有效地模拟过程,并能够迅速找到接近最优值的结果。