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Development of a modified ant colony algorithm for order scheduling in food processing plants

Korobiichuk Igor, Hrybkov Serhii, Seidykh Olga, Ovcharuk Volodymyr, Ovcharuk Andrii

Journal of Automation Mobile Robotics and Intelligent Systems

2022

Vol. 16, No. 1

53--61

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.

Features of control processes in organizational-technical (technological) systems of continuous type

Korobiichuk Igor, Ladanyuk Anatoliy, Boiko Regina, Hrybkov Serhii

Journal of Automation Mobile Robotics and Intelligent Systems

2020

Vol. 14, No. 4

11--17

Technological complexes of various industries are characterized by certain modes of operation (technological regulations), which correspond to the set of variables of different nature, which have a high-dynamics of change and determine the main technical and economic performance of the object. The aim of the research is to identify information software approaches to support decision-making in organizational-technical (technological) systems. Research results are obtained through grouping, generalization and comparison methods. The scientific significance of the results are to determine the objective need to use intelligent decision support subsystems to quickly manage complex organizational-technical systems based on both: clear and formalized data and knowledge and high-quality fuzzy estimates.