Development of a modified ant colony algorithm for order scheduling in food processing plants - Korobiichuk, Igor; Hrybkov, Serhii; Seidykh, Olga; Ovcharuk, Vladimir; Ovcharuk, Andrii (My University, 2022)
This developed modified ant colony algorithm includes an additional improvement with local optimization methods, which reduces the time required to find a solution to the problem of optimization of combinatorial order sequence planning in a food enterprise. The planning problem requires consideration of a number of partial criteria, constraints, and an evaluation function to determine the effectiveness of the established version of the order fulfillment plan. The partial criteria used are: terms of storage of raw materials and finished products, possibilities of occurrence and processing of substandard products, terms of manufacturing orders, peculiarities of fulfillment of each individual order, peculiarities of use of technological equipment, expenses for storage and transportation of manufactured products to the end consumer, etc. The solution of such a problem is impossible using traditional methods. The proposed algorithm allows users to build and reconfigure plans, while reducing the time to find the optimum by almost 20% compared to other versions of algorithms
Keywords: order fulfillment planning; modified ant colony algorithm; efficiency of the algorithms; optimization; food industry; кафедра інформаційних технологій, штучного інтелекту і кібербезпеки