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Synthesis Production Schedules Based on Ant Colony Optimization Method

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 573)


It is proposed to use ant algorithms together with the object-oriented simulation models. To optimize the functioning of the automated technological complex machining together with a modified ant algorithm it is designed object model, which allows to calculate the fitness function and evaluate potential solutions. The transition and calculation of the concentration for synthetic pheromone rules are determined for supposed directed ant algorithms.


  • Natural computing
  • Ant colony algorithm
  • Production schedules component
  • Flexible manufacturing systems

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  • DOI: 10.1007/978-3-319-57261-1_45
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The research described in this paper is partially supported by the Russian Foundation for Basic Research (grants 15-07-08391, 15-08-08459, 16-07-00779, 16-08-00510, 16-08-01277, 16-29-09482-ofi-i, 17-08-00797, 17-06-00108, 17-01-00139, 17-20-01214), grant 074-U01 (ITMO University), project 6.1.1 (Peter the Great St.Petersburg Polytechnic University) supported by Government of Russian Federation, Program STC of Union State “Monitoring-SG” (project 1.4.1-1, project 6MCГ/13-224-2), state order of the Ministry of Education and Science of the Russian Federation № 2.3135.2017/K, state research 0073–2014–0009, 0073–2015–0007, International project ERASMUS +, Capacity building in higher education, № 73751-EPP-1-2016-1-DE-EPPKA2-CBHE-JP, Innovative teaching and learning strategies in open modelling and simulation environment for student-centered engineering education.

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Correspondence to Vadim Skobtsov .

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Skobtsov, Y., Chengar, O., Skobtsov, V., Pavlov, A.N. (2017). Synthesis Production Schedules Based on Ant Colony Optimization Method. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Artificial Intelligence Trends in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 573. Springer, Cham.

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