Estimation of the Execution Time of Encryption, Decryption, and Homomorphic Calculations Using the Domingo-ferrer Cryptosystem
Year: 2024
Type: article
Abstract: One of the main conditions for the successful functioning of the enterprise is a well-organized productionplanning process. Production planning systems of the APS/MES class, the basis of which are algorithmsfor building production plans, allow automating this activity. The paper examines the problem ofscheduling for enterprises of a discrete type of production, related to the field of multi-criteria optimizationproblems. A formal description of the planning task is given, taking into account the main productionconstraints (time constraints, equipment requirements and the order of operations). The main methods ofsolving problems of this class are briefly considered; their main advantages and disadvantages are noted.To solve this problem, an approach based on the generation of heuristic rules used in planning productionoperations for specified resources has been chosen. Based on this approach, a two-stage algorithm forbuilding production schedules is proposed, which includes the generation of dispatching rules and theirfurther application in building schedules. A genetic algorithm is responsible for generating dispatch rules.The implementation of its genetic operators is described in detail, as well as the composition of the chromosome and the tree representation of the dispatch rules included in the chromosome. The algorithm isimplemented in C# 12 using a free platform.NET 8. The implemented algorithm has shown its effectivenessin comparison with the greedy algorithm on small generated datasets. Further research in this area isaimed at evaluating the effectiveness of the constructed algorithm with more complex genetic operatorsand the structure of the expression tree, as well as reducing the duration of the process of generating heuristicrules for large data sets.
Authors: L. K. Babenko, V. S. Starodubcev
Institution: Southern Federal University
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4406397391