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

• Autorzy: Korobiichuk Igor , Hrybkov Serhii , Seidykh Olga , Ovcharuk Volodymyr , Ovcharuk Andrii

Identyfikatory

DOI

10.14313/JAMRIS/1-2022/6

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

order fulfillment planning; modified ant colony algorithm; efficiency of the algorithms; optimization; food industry

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2022
• Tom: Vol. 16, No. 1
• Strony: 53--61
• Opis fizyczny: Bibliogr. 33 poz., rys.

Twórcy

autor

Korobiichuk Igor

• ŁUKASIEWICZ Research Network – Industrial Research Institute for Automation and Measurements PIAP, Jerozolimskie 202, 02-486 Warsaw, Poland

autor

Hrybkov Serhii

• Ukrainian State University of Food Technologies, 68 Volodymyrska Street, 01033, Kyiv, Ukraine

autor

Seidykh Olga

• Ukrainian State University of Food Technologies, 68 Volodymyrska Street, 01033, Kyiv, Ukraine

autor

Ovcharuk Volodymyr

• Ukrainian State University of Food Technologies, 68 Volodymyrska Street, 01033, Kyiv, Ukraine

autor

Ovcharuk Andrii

• Ukrainian State University of Food Technologies, 68 Volodymyrska Street, 01033, Kyiv, Ukraine

Bibliografia

• [1] A. Oliinyk, S. Skrupsky, S. Subbotin, I. Korobiichuk, “Parallel Method of Production Rules Extraction Based on Computational Intelligence”, Automatic Control and Computer Sciences, 2017, Vol. 51, No. 4, 2017, pp. 215–223. 10.3103/S0146411617040058
• [2] I. Korobiichuk, A. Ladaniuk, V. Ivashchuk, “Features of Control for Multi-assortment Technological Process”, n: Szewczyk R., Krejsa J., Nowicki M., Ostaszewska-Liżewska A. (eds) Mechatronics 2019: Recent Advances Towards Industry 4.0. MECHATRONICS 2019. Advances in Intelligent Systems and Computing, vol 1044. Springer, Cham, 2020, pp. 214-221. 10.1007/978-3-030-29993-4_27
• [3] I. Korobiichuk, A. Ladanyuk, N. Zaiets, L. Vlasenko, “Modern development technologies and investigation of food production technological complex automated systems”. In: ACM International Conference Proceeding Series. 2nd International Conference on Mechatronics Systems and Control Engineering ICMSCE 2018, February 21-23, 2018, Amsterdam, Netherlands. 52-57, 10.1145/3185066.3185075
• [4] V. Tregub, I. Korobiichuk, O. Klymenko, A. Byrchenko, K. Rzeplińska-Rykała, “Neural Network Control Systems for Objects of Periodic Action with Non--linear Time Programs”. In: Szewczyk R., Zieliński C., Kaliczyńska M. (eds) Automation 2019. AUTOMATION 2019. Advances in Intelligent Systems and Computing, vol 920. Springer, Cham, pp. 155-164 (2020), 10.1007/978-3-030-13273-6_16
• [5] I. Korobiichuk, A. Lobok, B. Goncharenko, N. Savitska, M. Sych, L. Vihrova, “The Problem of the Optimal Strategy of Minimax Control by Objects with Distributed Parameters”. In: Szewczyk R., Zieliński C., Kaliczyńska M. (eds) Automation 2019. AUTOMATION 2019. Advances in Intelligent Systems and Computing, vol 920. Springer, Cham, 2020, pp. 77-85. 10.1007/978-3-030-13273-68
• [6] I. Korobiichuk, N. Lutskaya, A. Ladanyuk, S. Naku, M. Kachniarz, M. Nowicki, R. Szewczyk, “Synthesis of Optimal Robust Regulator for Food Processing Facilities”. In: Advances in Intelligent Systems and Computing, Vol. 550, ICA 2017: Automation 2017, pp. 58-66. 10.1007/978-3-319-54042-9_5
• [7] S. Hrybkov, O. Kharkianen, V. Ovcharuk, I. Ovcharuk, “Development of information technology for planning order fulfillment at a food enterprise”, Eastern-European Journal of Enterprise Technologies, vol. 1/3, no. 103, 2020, pp. 62–73. 10.15587/1729-4061.2020.195455
• [8] S. Hrybkov, V. Lytvynov, H. Oliinyk, “Web-oriented decision support system for planning agreements execution”, Eastern-European Journal of Enterprise Technologies, vol. 3/2, no. 99, 2018, pp. 13–24. 10.15587/1729-4061.2018.132604
• [9] O. Kharkianen, O. Myakshylo, S. Hrybkov, M. Kostikov, “Development of information technology for supporting the process of adjustment of the food enterprise assortment”, Eastern-European Journal of Enterprise Technologies, vol. 1/3,no. 91, 2018, pp. 77–87. 10.15587/1729-4061.2018.123383
• [10] K. Senthilkumar, V. Selladurai, K. Raja, V. Thirunavukkarasu, “A Hybrid Algorithm Based on PSO and ACO Approach for Solving Combinatorial Fuzzy Unrelated Parallel Machine Scheduling Problem”, European Journal of Scientific Research, vol. 2, no. 64, 2011, pp. 293-313.
• [11] F. Rodriguez, M. Lozano, C. García-Martínez, J. González-Barrera, “An artificial bee colony algorithm for the maximally diverse grouping problem”, Information Sciences, no. 230, 2013, pp. 183–196. 10.1016/j.ins.2012.12.020
• [12] Yang-Kuei Lin, “Scheduling efficiency on correlated parallel machine scheduling problems”, Operational Research, vol. 18, 2018, pp. 603–624. 10.1007/s12351-017-0355-0
• [13] T. Zheldak, “Application of the method of modeling the ant colony to the solution of combinatorial problems scheduling the execution of order by metallurgical plants”. Mathematical Machines and Systems, vol. 4, 2013, pp. 95–106.
• [14] G. Georgiadis, A. Elekidis, M. Georgiadis, “Optimization-Based Scheduling for the Process Industries: From Theory to Real-Life Industrial Applications”, Processes, vol. 7, 2019, pp. 1–35. 10.3390/pr7070438.
• [15] Pintea C-M., Advances in Bio-inspired Computing for Combinatorial Optimization Problem, Springer: Berlin, 2014, p. 188. 10.1007/978-3-642-40179-4.
• [16] S. Talatahari, “Optimum Performance-Based Seismic Design of Frames Using Metaheuristic Optimization Algorithms”, Metaheuristic Applications in Structures and Infrastructures, 2013, pp. 419–437. 10.1016/B978-0-12-398364-0.00017-6
• [17]. K. Jha. Manoj, “Metaheuristic Applications in Highway and Rail Infrastructure Planning and Design: Implications to Energy and Environmental Sustainability”, Metaheuristics in Water, Geotechnical and Transport Engineering, 2013, pp. 365-384. 10.1016/B978-0-12-398296-4.00016-7
• [18] V. Kureichik, A. Kazharov, “Using Fuzzy Logic Controller in Ant Colony Optimization”, ArtificialIntelligence Perspectives and Applications, 2015, pp. 151–158. 10.1007/978-3-319-18476-0_16
• [19] V. Kureichik, A. Kazharov, “The Development of the Ant Algorithm for Solving the Vehicle Routing Problems”, World Applied Sciences Journal, vol. 26, no. 1, 2013, pp. 114–121. 10.5829/idosi. wasj.2013.26.01.13468
• [20] T. Stutzle, H. Hoos, “Max-min ant system”, Future Generation Computer Systems, vol. 8, no. 16, 2000, pp. 889–914.
• [21] K. Rocki, R. Suda, “Accelerating 2-opt and 3-opt Local Search Using GPU in the Travelling Salesman Problem”, IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2012, p. 705–706. 10.1109/CCGrid.2012.133
• [22] F. Rodriguez, M. Lozano, C. García-Martínez, J. González-Barrera, “An artificial bee colony algorithm for the maximally diverse grouping problem”, Information Sciences, 230, 2013, pp. 183–196. 10.1016/j.ins.2012.12.020
• [23] I. Fister, D. Fister, X.-S. Yang, “A hybrid bat algorithm”, Electrotechnical Review, vol. 1–2, no. 80, 2013, pp. 1–7.
• [24] G. Wang, L. Guo, “A Novel hybrid bat algorithm with harmony search for global numerical optimization”. Hindawi Publishing Corporation, 2013, pp. 1–21. 10.1155/2013/696491
• [25] X.-S. Yang, X. He, “Bat algorithm: literature review and applications”, International Journal of Bio-Inspired Computation, vol. 5, no. 3, 2013, pp. 141–149. 10.1504/IJBIC.2013.055093
• [26] X.-S. Yang, H. Gandomi, “Chaotic bat algorithm”, Journal of Computational Science, vol. 5, no. 2, 2014, pp. 224–232. 10.1016/j.jocs.2013.10.002
• [27] Y. Zhang, S. Balochian, P. Agarwal, V. Bhatnagar, O.Housheya, “Artificial Intelligence and Its Applications”, Mathematical Problems in Engineering, vol. 2014, pp. 1–10. 10.1155/2014/840491
• [28] Y. Virginia, A. Analía, “Deterministic crowding evolutionary algorithm to form learning teams in a collaborative learning context”, Expert System Appl., vol. 10, no. 39, 2012, pp. 8584-8592. 10.1016/j.eswa.2012.01.195
• [29] Y. Jie, K. Nawwaf, P. Grogono, “Bi-objective multi population genetic algorithm for multimodal function optimization”, IEEE Trans. Evol. Comput., vol. 1, no. 14, 2010, pp. 80–102. 10.1109/TEVC.2009.2017517
• [30] W. Hu-Sheng, Z. Feng-Ming, “Wolf Pack Algorithm for Unconstrained Global Optimization”, Mathematical Problems in Engineering, vol.2014, pp. 1–17. 10.1155/2014/465082
• [31] S. Mirjalili, A. Lewis, “Grey Wolf Optimizer”, Advances in Engineering Software, vol. 69,2014, pp. 46–61. DOI: 10.1016/j.advengsoft.2013.12.007
• [32] A. Madadi, M. Motlagh, “Optimal Control of DC motor using Grey Wolf Optimizer Algorithm”, Technical Journal of Engineering and Applied Science, vol. 4, no. 4, 2014, pp. 373–379.
• [33] М. Gendereau, J. I. Potvin, “Handbook of Metaheuristic”, 3rd ed., Springer International Publishing: Cham, 2019, p. 604. 10.1007/978-3-319-91086-4

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).