SHS Web of Conf.
Volume 44, 2018IV International Scientific Conference “The Convergence of Digital and Physical Worlds: Technological, Economic and Social Challenges” (CC-TESC2018)
|Number of page(s)||9|
|Published online||05 June 2018|
Digital transformation and optimization models in the sphere of logisticsa
1 Peter the Great St. Petersburg Polytechnic University, 195251 Polytechnicheskaya st. 29, Russian Federation
2 Peoples Friendship University of Russia (RUDN University), 117198 Miklukho-Maklaya st. 6, Russian Federation
* Corresponding author: email@example.com
The efficiency, optimization, speed and time limits have always been of crucial importance for the logistics system, while saving of speed and time in the real-time mode are the key factors with transition to digital technologies and establishment of Industry 4.0 since they become the competitive advantages. The innovative use of technologies in such fields as data analysis, Internet of things and cloud calculations significantly change the logistical and transportation systems as a result of mating digital and existing supply chains becoming the catalyst of transition to “Logistika 4.0”. This work offers a model and method of shaping an optimal plan of fulfilling a complex of interrelated logistical operations for such changing conditions.The model is based on the presentation of optimization procedure as a non-linear task of discrete programming consisting in minimization of time of fulfilling the above complex of operations by a limited number of contractors partially interchangeable under conditions of limited budgeting. A model obtained thereat for establishing an optimal plan will belong to the class of nonpolynimially challenging tasks. In order to solve these tasks, a method has been suggested supported by a procedure of branches and boundaries. Thealgorithmisbasedon dichotomous branchingdiagram. Itsapplicationprovidesforreceivingboth quasi-optimalandoptimallogisticsplansfor the finite number of steps. Atthat, theassessmentofaccuracy is provided for quasi-optimal plans. The proposed model and method help solve a wide spectrum of practical tasks of logistical planning under conditions of digital transformation.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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